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Journal articles on the topic 'Google Colab'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

Amal, Bahar, Silvia Damayanti, Aisyah Nabila Khonsa, et al. "Penilaian Mahasiswa PBSI Unsika Terhadap Keefektifan Penggunaan Google Colab Dalam Pembelajaran Coding." Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) 6, no. 1 (2025): 66–76. https://doi.org/10.30645/kesatria.v6i1.547.

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The skills of processing and analyzing data are very important in various sectors, including education. Students of Indonesian Language and Literature Education (PBSI) use google colab to study data processing. The purpose of this research is to understand and analyze the assessment of using google colab in coding learning for students of the Indonesian Language and Literature Education (PBSI) with the research object limited to students from the 2022 and 2023 batches. The research method used is quantitative with a questionnaire as the data collection tool. The questionnaire consists of open-

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Robi Padri, Abdul, Asro Asro, and Indra Indra. "Classification of Traffic Congestion in Indonesia Using the Naive Bayes Classification Method." Journal of World Science 2, no. 6 (2023): 877–88. http://dx.doi.org/10.58344/jws.v2i6.285.

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The purpose of this research is to analyze the accuracy of congestion data using Google Colab in detecting congestion by the province in Indonesia the author tries to test strategies for dealing with congestion in the Indonesian region by utilizing the Naïve Bayes method. In this journal, apply with Google Collab . This research uses data that comes from crawling data on Twitter. Using the Naive Bayes method to find the shortest route is efficient and not congested. Implementation of online school transportation using the naive Bayes method in minimizing travel costs to pick up students can re

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Miftahul Arifin, Fauzi Helmi, and Dafiq Fajri Alamsyah. "ANALISIS POLA ASOSIASI PENJUALAN PRODUK RITEL DENGAN PLATFORM GOOGLE COLAB." JUSTIFY : Jurnal Sistem Informasi Ibrahimy 3, no. 1 (2024): 74–85. http://dx.doi.org/10.35316/justify.v3i1.5569.

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Minimarket Assalafi menghadapi penurunan penjualan dan belum memiliki sistem pengolahan data penjualan yang efektif untuk menghasilkan aturan asosiasi. Penelitian ini bertujuan untuk meningkatkan penjualan melalui analisis pola pembelian pelanggan dengan menggunakan Algoritma Apriori. Data yang digunakan adalah sampel penjualan dalam format Microsoft Excel yang mencakup 178.798 record dari 55.989 transaksi. Pengolahan data dilakukan melalui beberapa tahapan di Google Colab, termasuk impor data, seleksi data, pembersihan data, pra-pemrosesan, dan menjalankan algoritma data mining. Penelitian in

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Sytnykova, Yuliia, Vitalii Kyrpenko, Serhii Palevych, Olha Pochuieva, Svitlana Lamtiuhova, and Olena Chaika. "Implementation of Professionally Oriented Tasks with Interactive Cloud Environment Google Colab." International Journal of Interactive Mobile Technologies (iJIM) 19, no. 09 (2025): 73–91. https://doi.org/10.3991/ijim.v19i09.53459.

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The purpose of the paper is to analyze the necessity of implementing professionally oriented tasks in higher mathematics courses for technical students during practical classes using the interactive cloud environment Google Colab. The results are as follows. The main mathematical concepts are analyzed; the indicators of professionally oriented mathematical tasks are characterized; the aspects of solving professionally oriented tasks are considered. The students’ survey as a pilot study has shown that students do not have very high self-esteem, have little problem-solving skills, it affects stu

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Octarina, Sisca, Fitri Maya Puspita, Evi Yuliza, and Indrawati Indrawati. "PENDAMPINGAN PENGGUNAAN GOOGLE COLAB PADA PEMBELAJARAN PYTHON DAN MACHINE LEARNING BAGI DOSEN MATEMATIKA DI PALEMBANG." Jurnal Pepadu 6, no. 1 (2025): 56–66. https://doi.org/10.29303/pepadu.v6i1.6457.

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Pembelajaran dan penelitian di perguruan tinggi mengalami banyak tantangan dan masalah, terutama di masa setelah pandemi Covid-19. Namun, seiring berjalannya waktu, tantangan ini dapat diatasi dengan menggunakan platform pembelajaran online seperti Moodle University, Zoom, Google Meeting, dan Microsoft Teams. Akan tetapi, di bidang penelitian, hal ini belum sepenuhnya diselesaikan. Terkadang sulit bagi tim peneliti untuk bekerja sama dalam penelitian. Catatan penelitian atau logbook penelitian tidak mudah dikirim melalui email. Selain itu, catatan penelitian seperti pemrograman komputer, membu

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Hewitt, Christopher. "Exploring Canadian Geospatial Data with GeoPandas in Colab Notebooks." Bulletin - Association of Canadian Map Libraries and Archives (ACMLA), no. 173 (April 1, 2024): 14–17. http://dx.doi.org/10.15353/acmla.n173.5671.

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Google Colab with the GeoPandas Python package is an effective platform for GIS analysis. Following a tutorial prepared by the author, this review discusses how users can load, project, query and visualize GIS data through graphs and maps. Future directions of where this platform could be taken are also discussed. Lastly, the benefits and drawbacks of GIS analysis with Google Colab are presented.

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Abdillah, T. Rafli. "Analisis Komparasi Cycles X Render Dan Cycles Render Menggunakan Google Colab." Jurnal TIKA 8, no. 1 (2023): 90–94. http://dx.doi.org/10.51179/tika.v8i1.1937.

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Mesin render yang baik dan cepat sangat dibutuhkan dalam dunia 3D rendering. Dalam artikel ini, kami melakukan analisis komparasi antara dua mesin render yang populer yaitu Cycles X dan Cycles menggunakan Google Colab. Google Colab adalah platform gratis yang dapat digunakan untuk mengakses mesin render pada server jarak jauh dengan akses GPU. Dalam penelitian ini, kami menggunakan file objek dan pengaturan yang sama pada kedua mesin render untuk membandingkan waktu render dan kualitas render. Hasil pengujian menunjukkan bahwa Cycles X lebih cepat daripada Cycles dalam melakukan render pada ob

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Rangga Gelar Guntara. "Visualisasi Data Laporan Penjualan Toko Online Melalui Pendekatan Data Science Menggunakan Google Colab." ULIL ALBAB : Jurnal Ilmiah Multidisiplin 2, no. 6 (2023): 2091–100. https://doi.org/10.56799/jim.v2i6.1578.

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Penelitian ini membahas tentang visualisasi data menggunakan Google Colab dengan pendekatan data science pada laporan penjualan toko online. Tujuan penelitian ini adalah untuk menunjukkan bahwa visualisasi data yang baik dapat memberikan wawasan yang lebih dalam tentang pola penjualan dan tren pada toko online serta membantu dalam pengambilan keputusan yang lebih baik di masa depan. Penelitian ini menggunakan dataset penjualan toko online yang dimanipulasi menggunakan Python dan Google Colab. Beberapa jenis grafik dan visualisasi data yang dibuat antara lain bar chart, line chart, scatter plot

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Rivera Demanuel, Diego Richard, Cleofe Huamani Huancara, and Yimy Alfredo Charca Ccama. "Sistema automático para calificación de vino mediante Redes Neuronales." Innovación y Software 3, no. 1 (2022): 30–46. http://dx.doi.org/10.48168/innosoft.s8.a51.

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Tratamiento de datos para la calificación de vinos, este informe detalla el proceso seguido, en donde se utilizó el lenguaje de programación Phyton, para el análisis de los datos del dataset, se utilizó el servidor Google Colab para ejecutar los algoritmos en la nube ya que el equipo considero que la velocidad de análisis de datos en google colab es más rápido. Las redes neuronales tienen capacidad de aprender y realizar tareas basadas en un entrenamiento inicial llamado aprendizaje adaptativo y además de que son tolerantes a los fallos.

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Rangga Gelar Guntara. "Pelatihan Sains Data Bagi Pelaku UMKM di Kota Tasikmalaya Menggunakan Google Colab." Joong-Ki : Jurnal Pengabdian Masyarakat 2, no. 2 (2023): 245–51. http://dx.doi.org/10.56799/joongki.v2i2.1572.

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Tujuan dari pelatihan ini adalah untuk memberikan pengetahuan dan keterampilan dasar tentang sains data kepada pelaku UMKM agar mereka dapat memanfaatkannya dalam pengembangan bisnis mereka. Dalam pengabdian ini, dijelaskan langkah-langkah pelatihan sains data menggunakan Google Colab, mulai dari pengenalan dasar tentang sains data, pemrosesan data, eksplorasi data, hingga pembuatan model prediksi sederhana. Banyak manfaat dari penggunaan Google Colab dalam pelatihan sains data, seperti kemudahan akses dan penggunaan alat analisis data yang canggih. Hasil dari pelatihan ini menunjukkan bahwa p

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ณัฐกานต์ ธีระทานันท์, ณัฐกานต์, та พีรยศ ภมรศิลปธรรม. "การประยุกต์ใช้ ChatGPT และ Google Colab สร้างอัลกอริทึม คำนวณการจัดกลุ่มและจัดลำดับเส้นทางตรวจสถานที่ขายยาแผนปัจจุบัน: กรณีศึกษาของสำนักงานสาธารณสุขจังหวัดปทุมธานี". Thai Bulletin of Pharmaceutical Sciences 20, № 1 (2025): 55–65. https://doi.org/10.69598/tbps.20.1.55-65.

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การตรวจประเมินสถานที่ขายยาแผนปัจจุบัน (ขย.1) เป็นภารกิจในการกำกับดูแลคุณภาพและมาตรฐานของสำนักงานสาธารณสุขจังหวัด การวางแผนเส้นทางในปัจจุบันใช้ผู้ที่มีประสบการณ์หรือชำนาญเส้นทางเป็นหลัก การเพิ่มประสิทธิภาพการทำงานเป็นความท้าทายอย่างหนึ่ง การศึกษานี้มีวัตถุประสงค์เพื่อพัฒนาวิธีการโดยสร้างอัลกอริทึมด้วย ChatGPT และคำนวณผ่าน Google Colab เพื่อจัดกลุ่ม และจัดลำดับเส้นทาง เปรียบเทียบประสิทธิภาพของการวางแผนเส้นทางโดยผู้เชี่ยวชาญที่มีใช้อยู่ในปัจจุบัน กับอัลกอริทึมทางคอมพิวเตอร์ที่มี 3 แบบ นำไปคำนวณระยะทางใน Google map เพื่อศึกษาระยะทางและระยะเวลาที่ใช้เดินทางสำหรับการตรวจสถานที่ขายยาแผนปัจจุบัน งานวิ

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Az Zahra, Aulia, Nabila Istiana, and Ari Wibowo. "Implementasi Interpolasi Polinomial Bentuk Baku dan Metode Selisih Terbagi Newton Menggunakan Excel dan Google Colab." GAUSS: Jurnal Pendidikan Matematika 8, no. 1 (2025): 1–13. https://doi.org/10.30656/gauss.v8i1.10589.

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Abstrak Penelitian ini bertujuan menganalisis serta membandingkan efektivitas penerapan metode interpolasi polinomial bentuk baku dan metode selisih terbagi Newton memakai dua perangkat bantu: Microsoft Excel dan Google Colab. Interpolasi polinomial adalah cara numerik yang dipakai guna menaksir nilai fungsi dari titik-titik data khusus. Penelitian ini menggunakan suatu pendekatan kualitatif dengan suatu metode studi literatur untuk mengkaji teori, algoritma, serta penerapan praktis dari masing-masing metode tersebut. Hasil analisis menunjukkan bahwa kedua metode tersebut mampu memberikan hasi

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Johary, Rosa, Christophe Révillion, Thibault Catry, et al. "Detection of Large-Scale Floods Using Google Earth Engine and Google Colab." Remote Sensing 15, no. 22 (2023): 5368. http://dx.doi.org/10.3390/rs15225368.

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This paper presents an operational approach for detecting floods and establishing flood extent using Sentinel-1 radar imagery with Google Earth Engine. The methodology relies on change detection, comparing pre-event and post-event images. The change-detection method is based on the normalised difference ratio. Additionally, the HAND model is employed to delineate zones for processing only in flood-prone areas. The approach was tested and calibrated at a small scale to optimise parameters. In these calibration tests, an accuracy of 85% is achieved. The approach was then applied to the whole of

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Uysal, Mustafa Mutlu, and Murat Uysal. "Uzaktan Algılama ve Veri Bilimi Teknikleriyle Orman Yangınları için Meteorolojik Etkilerin İzlenmesi." Afyon Kocatepe University Journal of Sciences and Engineering 25, no. 1 (2025): 137–43. https://doi.org/10.35414/akufemubid.1489084.

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Bu çalışmada uzaktan algılama veri ve teknikleriyle çalışma alanına özgü meteorolojik veri seti oluşturulup Google Colab ortamında python kodları kullanılarak orman yangınları için meteorolojik etkilerin izlenmesi amaçlanmıştır. Bu kapsamda Google Earth Engine Kataloğundan çalışma alanına ait Terra Climate görüntüleri aylık zamansal çözünürlükte indirilerek Arcmap yazlımı ile ön işleme yapılmıştır. Çalışma alanında gerçekleşmiş orman yangını koordinatları ile yangın var/yok noktası oluşturulmuştur. Bu noktalar bulunduğu pikseller için değer çıkarımı yapılarak Evapotranpirasyon, Rüzgâr hızı, To

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Recalde Mena, Juana del Rocío, and Ligia Vanessa Sánchez Parrales. "Uso de la simulación en Google Colab como herramienta tecnológica para la optimización de procesos administrativos de la Unidad Educativa Católica La Victoria." Código Científico Revista de Investigación 6, E1 (2025): 706–25. https://doi.org/10.55813/gaea/ccri/v6/ne1/714.

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La presente investigación examina el uso de Google Colab como herramienta tecnológica para optimizar los procesos administrativos en la Unidad Educativa Católica La Victoria. La digitalización de la gestión administrativa es un desafío clave en el sector educativo, y la implementación de plataformas basadas en la nube puede contribuir significativamente a la eficiencia operativa. El estudio adopta un enfoque mixto, combinando análisis cuantitativo y cualitativo para evaluar el impacto de las simulaciones en Google Colab. A través de encuestas y pruebas comparativas, se analizaron indicadores c

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Husna, Lailatul, and Pradita Eko Prasetyo Utomo. "Analisis Dan Visualisasi Data Body Performance Menggunakan Tiga Tools Visualisasi." Jurnal Ilmiah Intech : Information Technology Journal of UMUS 5, no. 1 (2023): 32–40. http://dx.doi.org/10.46772/intech.v5i1.1167.

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Artikel ini membahas tentang Analisa dan visualitasasi data dari data body performance .dimana nanntinya hasil Analisa penulis akan dicantumkan dibagian hasil dan pembahasan.dari artikel ini kita dapat melihat keuntungan memvisualisasikan data yang ada.dengan adanya beragam tools visualisasi data akan mempermudah kita dalam menganalisis dan memvisualisasikan data yang diinginkan.berikut tiga tools yang digunakan dalam artikel ini yaitu : Microsoft Power BI, Google Colab, dan Tableau Public.Adanya visualisasi data akan mempermudah mengambil keputusan.Dalam melakukan visualisasi data harus mempe

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Saharuddin, Saharuddin, and Medy Wisnu Prihatmono. "PENGENALAN DAN PELATIHAN DASAR BAHASA PEMROGRAMAN PYTHON PADA SISWA/I SMA NEGERI 3 MAKASSAR." SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan 6, no. 4 (2022): 2233. http://dx.doi.org/10.31764/jpmb.v6i4.10569.

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ABSTRAKPengabdian Kepada Masyarakat (PkM) merupakan salah satu bentuk pelaksanaan Trihdarma Perguruan Tinggi yang wajib dilakukan oleh dosen, pengabdian kepada masyarakat yang dulakukan ini adalah memberikan pengetahuan tentang dasar bahasa pemrograman phyton. Mata pelajaran informatika mencakup lima materi yang bakal menunjang kompetensi siswa di era revolusi industri 4.0. Yakni, teknik komputer, jaringan komputer/internet, analisis data, dampak sosial informatika, dan programming. Mata pelajaran Informatika sesuai dengan kebutuhan masa depan anak bangsa. SMAN 3 Makassar adalah salah satu SLT

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Chary, Podakanti Satyajith. "Real Time Object Detection Using YOLOv4." International Journal for Research in Applied Science and Engineering Technology 11, no. 12 (2023): 1375–79. http://dx.doi.org/10.22214/ijraset.2023.57602.

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Abstract: This research paper introduces a robust real-time object detection system, leveraging the cutting-edge capabilities of the YOLOv4 (You Only Look Once) deep learning framework.The integration of this system with a webcam in the Google Colab environment forms a novel and accessible platform for live object detection. The paper meticulously details the methodology behind theintegration, providing comprehensive insightsinto the intricatesteps taken to achieve seamless real-time detection. Key aspects covered include the configuration and acquisition of YOLOv4 model weights, setup of the

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Safitri, Raudhatun, Puguh Wahyu Prasetyo, Dian Eka Wijayanti, Samsul Arifin, Fariz Setyawan, and Joe Repka. "Text security by using a combination of the vigenere cipher and the rubik's cube method of size 4×4×4." Al-Jabar : Jurnal Pendidikan Matematika 14, no. 2 (2023): 281. http://dx.doi.org/10.24042/ajpm.v14i2.14276.

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Background: In the current era of technology, information security is increasingly important. The growth of technology leads to a higher level of threat to the security of data and information dissemination, and cryptography is a valuable protective tool.Aim: The primary objective of this research is to enhance text security through the fusion of the Vigenere cipher and the Rubik's cube algorithm. By leveraging this novel approach, we aim to fortify the confidentiality of textual data against potential eavesdroppers and adversaries. To demonstrate the practicality of this method, we perform a

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Damayanti, Awis, and Agung Prabowo. "Analisis Perubahan Iklim: Frekuensi Bencana Alam dan Kerugian Ekonomi Menggunakan Google." PROSIDING SEMINAR NASIONAL SAINS DATA 4, no. 1 (2024): 662–68. https://doi.org/10.33005/senada.v4i1.299.

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Penelitian ini menganalisis dampak perubahan iklim terhadap frekuensi bencana alam dan kerugian ekonomi global dari tahun 2000 hingga 2018. Tujuannya adalah untuk memahami pola dan tren yang terkait, menggunakan pendekatan analisis data eksploratif dengan Google Colab untuk mendukung strategi mitigasi dan adaptasi yang lebih efektif. Penelitian ini menggunakan metode CRISP-DM, yang melibatkan langkah-langkah pemahaman bisnis, pemahaman data, persiapan data, pemodelan, evaluasi, dan penerapan. Data dianalisis menggunakan Google Colab dengan model regresi linier untuk memahami hubungan antara pe

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Padri, Abdul Robi. "KLASIFIKASI KEMANCETAN LALU LINTAS DI INDONESIA MENGGUNAKAN METODE NAIVE BAYES CLASSIFICATION." Simetris: Jurnal Teknik Mesin, Elektro dan Ilmu Komputer 14, no. 2 (2023): 297–310. http://dx.doi.org/10.24176/simet.v14i2.10102.

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ABSTRACTTujuan dari penelitian ini untuk data menganalisis akurasi kemancetan menggunakan google colab dalam mendeteksi kemacetan berdasarkan provinsi di indonesia, penulis mencoba menguji strategi dalam menangani Kemacetan wilayah indonesia, dengan memanfaatkan metode naïve bayes. Pada jurnal ini menerapkan dengan google colab. Penelitian ini memakai data yang bersumber dari crawling data di twiter. Penggunaan metode naive bayes dalam mencari Rute terpendek efesien dan tidak mancet. Penerapan Angkot Sekolah online menggunakan Metode naive bayes dalam Minimalisir Biaya Perjalanan menjemput Sis

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Ray, Sujan, Khaldoon Alshouiliy, and Dharma P. Agrawal. "Dimensionality Reduction for Human Activity Recognition Using Google Colab." Information 12, no. 1 (2020): 6. http://dx.doi.org/10.3390/info12010006.

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Human activity recognition (HAR) is a classification task that involves predicting the movement of a person based on sensor data. As we can see, there has been a huge growth and development of smartphones over the last 10–15 years—they could be used as a medium of mobile sensing to recognize human activity. Nowadays, deep learning methods are in a great demand and we could use those methods to recognize human activity. A great way is to build a convolutional neural network (CNN). HAR using Smartphone dataset has been widely used by researchers to develop machine learning models to recognize hu

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Maradi, Shivanand. "A Comparative Implementation of Iris Flower Classification Across Platform." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 01 (2025): 1–9. https://doi.org/10.55041/ijsrem41151.

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This paper presents a comparative analysis of the Iris Flower Classification problem implemented across three distinct computational platforms: classical computing using Jupyter Notebook, cloud computing via Google Colab, and quantum computing leveraging IBM Qiskit. The study evaluates the platforms based on execution efficiency, classification accuracy, and scalability. While classical and cloud-based implementations yielded similar performance metrics, the quantum approach demonstrated unique computational characteristics and challenges, such as noise and resource limitations. This research

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Hancco Vargas, Corina, David Flores Silva, Jessica Hancco Velásquez, and Alejandra Fernandez Ninahuaman. "Aplicación de árboles de decisión para un pronóstico salarial." Innovación y Software 4, no. 2 (2023): 153–65. http://dx.doi.org/10.48168/innosoft.s12.a112.

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Este artículo detalla el proceso que se realizó para el pronóstico salarial en una base de datos de un censo dado en 1996, donde se utilizó el lenguaje de programación Python, para el análisis de los datos del dataset se utilizó el servidor Google Colab para ejecutar los algoritmos en la nube, ya que el equipo considero que la velocidad de análisis de datos en Google Colab es más rápido. También se hizo uso de una de las técnicas de minería de datos para clasificar las variables usando árboles de decisión que tienen la capacidad de representar gráficamente varias soluciones alternativas con el

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Donal, O. D., L. M. Kamarudin, A. Zakaria, and N. Azmi. "Automated Detection of Floating Wood Logs on River Surfaces using YOLOv5 Model for Flood Warning System." Journal of Physics: Conference Series 2641, no. 1 (2023): 012011. http://dx.doi.org/10.1088/1742-6596/2641/1/012011.

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Abstract In Sabah and Sarawak, Malaysia, log transportation by rivers poses risks due to log fragmentation. This can obstruct water flow, causing navigation problems and flood risks during heavy rainfall. Current monitoring methods involve personnel at checkpoints but are slow. This project proposes an AI-based system using YOLO-v5 to detect intact logs and fragments on river surfaces. A dataset will be created by scraping websites and using Google Colab commands to download relevant keywords. Preprocessing includes data augmentation, contrast adjustment, noise reduction, and resolution standa

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Nasution, Adzkia Nur, Ardilla Syahfitri, and Zulfahmi Indra. "Implementasi Algoritma Kriptografi Modern melalui Google Colab: Studi Kasus AES dan RSA." Jurnal Multidisiplin Teknologi dan Arsitektur 2, no. 2 (2024): 841–45. http://dx.doi.org/10.57235/motekar.v2i2.3949.

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Di era digital yang semakin cepat, enkripsi modern memainkan peran penting dalam menjaga keamanan dan privasi data, terutama di lingkungan teknologi yang semakin saling terhubung dan kompleks. Dengan semakin banyaknya ancaman dunia maya, termasuk serangan malware, phishing, ransomware, dan upaya peretasan data yang semakin canggih, keamanan informasi telah menjadi prioritas utama. Algoritma enkripsi modern, seperti Advanced Encryption Standard (AES) dan Rivest-Shamir-Adleman (RSA) memastikan data terlindungi baik dari segi kerahasiaan, integritas, dan otentikasi. AES dikenal luas karena kecepa

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Kuroki, Masanori. "Using Python and Google Colab to teach undergraduate microeconomic theory." International Review of Economics Education 38 (November 2021): 100225. http://dx.doi.org/10.1016/j.iree.2021.100225.

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Ha, Myung Jeong. "Developing an English-Korean translation tool using GPT, API, and Google Colab." Secondary English Education 18, no. 1 (2025): 55–82. https://doi.org/10.20487/kasee.18.1.202502.55.

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Yuliyanah Sain, Aynun Andriani, and Nahla Nurhidayah. "Pelatihan Dasar Menganalisis Data dengan Mengunakan Google Colab di SMA Muhammadiyah Kendari." KREATIF: Jurnal Pengabdian Masyarakat Nusantara 3, no. 1 (2023): 01–08. http://dx.doi.org/10.55606/kreatif.v3i1.1163.

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Program Merdeka Belajar Kampus Merdeka (MBKM) merupakan bentuk pelaksanaan menteri pendidikan dan kebudayaan yang bertujuan mendorong mahasiswa untuk menguasai berbagai keilmuan untuk bekal memasuki dunia kerja. Yang wajib dilakukan oleh mahasiswa, pengabdian kepada masyarakat yang dilakukan ini adalah memberikan pengetahuan tentang dasar bahasa pemrograman phyton. Mata pelajaran informatika mencakup lima materi yang bakal menunjang kompetensi siswa di era revolusi industri 4.0. Yakni, teknik komputer, jaringan komputer/internet, analisis data, dampak sosial informatika, dan programming. Mata

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Peleshenko, Vitaly A. "ECONOMETRIC CALCULATIONS WITH INTEGRATION OF MACHINE LEARNING TECHNOLOGIES BASED ON GREYKITE ALGORITHMS ON THE EXAMPLE OF FORECASTING THE EXCHANGE RATE OF THE USD/RUB CURRENCY PAIR." SOFT MEASUREMENTS AND COMPUTING 8, no. 57 (2022): 68–76. http://dx.doi.org/10.36871/2618-9976.2022.08.007.

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The article is devoted to econometric calculations using machine learning technologies and GREYKITE libraries. The features of the integration of grey kit into the google colab development environment are considered, as well as the created econometric model for predicting the quotes of the USD/RUB currency pair.

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Aygün, Zeynep, Merve Kocaman, Salih Aydemir, and Berkant Konakoğlu. "Building Damage Detection Using Deep Learning Architecture with Satellite Images: The Case of the 6 February 2023 Kahramanmaraş Earthquake." International Journal of Pioneering Technology and Engineering 3, no. 02 (2024): 53–61. https://doi.org/10.56158/jpte.2024.94.3.02.

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Turkey is located in a region with a high density of fault lines, which makes it susceptible to a significant earthquake risk. The Kahramanmaraş earthquake on February 6, 2023, was one of the most devastating in recent years, causing extensive damage and loss. This study aims to support post-disaster rapid response and rescue operations by using deep learning techniques to detect and classify damaged and intact buildings from satellite images. Satellite images of the Kahramanmaraş and Antakya regions, with a resolution of 8192x4537, were obtained via Google Earth Pro. The images were labeled a

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Ariyanti, Maya, and Yumna Tazkia. "UNDERSTANDING SERVICE QUALITY OF MOBILE VIDEO EDITING : MAPPING THE NEGATIVE IMPRESSION BY TEXT MINING APPROACH." Jurnal Ilmiah Manajemen, Ekonomi, & Akuntansi (MEA) 8, no. 2 (2024): 1952–71. http://dx.doi.org/10.31955/mea.v8i2.4256.

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KineMaster is a video editing application that supports the content creator industry; however, compared to its competitors, that app falls short in release year, download numbers, and ratings. This research aims to determine the service quality of the Android-based KineMaster application based on sentiment analysis and the classification of mobile app service quality (MASQ) dimensions. The data used is secondary data from 5,000 reviews of Google Play Store using Google Colab and processed using RapidMiner Studi version 10.2. Naïve Bayes and k-Nearest Neighbors (KNN) algorithms are applied to d

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Rihastuti, Siti, Afnan Rosyidi, and Handoko Handoko. "Implementasi K-Nearest Neighbours Dengan Google Collab Untuk Klasifikasi Penyakit Kanker Payudara." Jurnal Teknologi Informasi 10, no. 2 (2025): 79–85. https://doi.org/10.52643/jti.v10i2.5223.

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Penelitian ini bertujuan untuik mengklasifikasi penyakit kanker payudara berdasarkan dataset pasien penderita penyakit kanker payudara menggunakan model K-Nearest Neigbors dan pengujian menggunakan Google Colab. Kanker payudara adalah salah satu jenis kanker yang paling umum di kalangan wanita dan deteksi dini sangat penting untuk meningkatkan peluang kesembuhan bagi penderitanya. Sebanyak 569 record dataset penyakit kanker payudara digunakan yang diambil dari situs kaggle. Terdapat 32 variabel yang ada didalam kriteria dataset yang akan diuji. Model KNN diterapkan dengan menentukan nilai K =

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Fajrizal, Susi Handayani, and Taslim. "PELATIHAN PEMROGRAMAN PYTHON DENGAN GOOGLE COLAB BAGI SISWA SMK INOVASI RIAU." J-COSCIS : Journal of Computer Science Community Service 4, no. 2 (2024): 133–41. http://dx.doi.org/10.31849/jcoscis.v4i2.19106.

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Pelatihan pemrograman Python untuk siswa SMK Inovasi Riau bertujuan untuk memberikan keterampilan dasar dalam pengembangan perangkat lunak menggunakan bahasa pemrograman Python dan menyiapkan siswa untuk karir di bidang teknologi informasi. Materi yang diajarkan dalam pelatihan ini meliputi pengenalan dasar tentang bahasa pemrograman Python, konsep dasar pemrograman seperti variabel, tipe data, penggunaan modul dan pustaka standar dalam Python. Selain materi tersebut, pelatihan pemrograman Python juga akan mencakup latihan dan proyek praktis untuk membantu siswa memahami dan menguasai konsep-k

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Gelindon, Jane B., Rose Mary A. Velasco, and Dionicio D. Gante. "Credit Risk Evaluation in Banking and Lending Sectors Using Neural Network Model." Journal of Corporate Finance Management and Banking System, no. 23 (May 31, 2022): 12–35. http://dx.doi.org/10.55529/jcfmbs23.12.35.

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This study presents the results of an experiment made with google colaboratory. The Google Colaboratory is also known as google colab it is a free online cloud-based Jupyter notebook environment that allows us to train our machine learning and deep learning models on CPUs, GPUs, and TPUs. We can determine the accuracy of the credit risk evaluation based on the dataset that was run in google colab using a neural network. The dataset has been thoroughly evaluated in creating a test harness for evaluating candidate models by calculating accuracy using k-fold cross-validation. When compared to a s

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Pessoa, Paulo Igor de Oliveira, and Edson Henrice. "Efficient Acceleration in Solving the 2D Neutron Diffusion Equation with CUDA: Exploring the Collaborative Practicality of Colab<i></i>." Brazilian Journal of Radiation Sciences 12, no. 4B (Suppl.) (2025): e2498. https://doi.org/10.15392/2319-0612.2024.2498.

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This paper explores an approach to accelerate the finite difference method applied to solving the two-dimensional (2D) neutron diffusion equation for two energy groups (2G) independent of time. The main innovation lies in the implementation of a performance optimization method, emphasizing the practicality of development in Python using direct browser collaboration through Google Colaboratory (Colab). Utilizing CUDA (Compute Unified Device Architecture) for GPU acceleration, we achieve significant computational performance improvements. The study compares Python implementations using CuPy and

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МОЛЧАНОВА, МАРИНА, ОЛЕКСАНДР МАЗУРЕЦЬ, ОЛЕНА СОБКО, ВАЛЕРІЯ КЛІМЕНКО, and ВЛАДИСЛАВ АНДРОЩУК. "Method for cyberbullying neuronetwork detection using cloud services and object-oriented model." Herald of Khmelnytskyi National University. Technical sciences 333, no. 2 (2024): 200–206. http://dx.doi.org/10.31891/2307-5732-2024-333-2.

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У роботі пропонується практичний підхід до виявлення кібербулінгу із використанням нейронної мережі BiLSTM, навченої за допомогою хмарних сервісів та застосунку, що реалізовує запропонований метод виявлення кібербулінгу. Для дослідження ефективності запропонованого методу було створено об’єктно-орієнтовану програмну реалізацію середовища програмування PyCharm, а також ноутбук для виконання в хмарному сервісі «Google Colab» для навчання нейромережі.

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Ariska, Melly, Hamdi Akhsan, Muhammad Muslim, Muhammad Romadoni, and Fena Siska Putriyani. "Prediksi Perubahan Iklim Ekstrem di Kota Palembang dan Kaitannya dengan Fenomena El Niño-Southern Oscillation (ENSO) Berbasis Machine Learning." JIPFRI (Jurnal Inovasi Pendidikan Fisika dan Riset Ilmiah) 6, no. 2 (2022): 79–86. http://dx.doi.org/10.30599/jipfri.v6i2.1611.

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The purpose of this study is to provide predictions of climate conditions and trend of temperature rise in the city of Palembang in the 21st century. The BMKG station data used, namely SK Palembang and SM SMB II from the 2000-2020 period were analyzed based on the agreement of the Expert Team for Climate Change Detection and Indices (ETCCDI). ). Analysis using google colab shows that rainfall in the city of Palembang has a fairly high variability and a decrease in the number of rainy days that occur in the city of Palembang with the trend of air temperature, namely TMAXmean and TMINmean, has i

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Susila, Anggara Budi, Haris Suhendar, and Riser Fahdiran. "Cloud-Based Teaching Tool of AlCu Band Gap Simulations Using GPAW: A Python-Driven Approach for Undergraduate Student." Jurnal Penelitian & Pengembangan Pendidikan Fisika 11, no. 1 (2025): 53–62. https://doi.org/10.21009/1.11105.

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This work introduces a computational teaching module that leverages Python, Google Colab, and the GPAW package to simulate the electronic band structure of AlCu materials. While powerful, traditional Density Functional Theory (DFT) tools like Quantum ESPRESSO or VASP often present steep learning curves and software installation challenges. By contrast, GPAW operating within Python and its seamless integration with Google Colab provides a user-friendly, platform-independent environment for students to explore quantum simulations without local setup requirements. The simulation workflow is highl

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Utomo, Rokhim, Mokhammad Syafaat, Kasiyanto Kasiyanto, Dekki Widiatmoko, and Rafi Maulana. "Cryptographic security analysis of the shift password method using the google colab application." TEKNOSAINS : Jurnal Sains, Teknologi dan Informatika 12, no. 1 (2025): 104–9. https://doi.org/10.37373/tekno.v12i1.1231.

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The study of information security methods to prevent unauthorized parties from reading it is known as cryptography. The Caesar Cipher method is a low-tech yet well-established cryptography technique. One of the earliest and most basic cryptographic methods is the Caesar Cipher, which substitutes a different letter with a specific alphabetic difference for each letter in the text. The Caesar Cipher is simple to comprehend and use, but it has a lot of flaws that leave it open to frequency analysis and brute force attacks. The purpose of this study is to use the Google Colab tool to examine the c

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G, DIVYA, and Dr VIJAYA. "MONITORING AND ANALYZING DIABETIC FOOT ULCER USING RESNET50 IN DEEP LEARNING." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 07, no. 10 (2023): 1–11. http://dx.doi.org/10.55041/ijsrem25998.

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This paper introduces a deep learning approach using the ResNet50 algorithm within Google Colab to detect diabetic foot ulcers. Early identification of these ulcers is crucial to prevent leg amputations. Leveraging a diverse dataset, the model exhibits high accuracy and sensitivity, offering a cost-effective solution for timely intervention in diabetic foot ulcers, there by improving patient outcomes.

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Elnashar, Abdelrazek, Hongwei Zeng, Bingfang Wu, et al. "Downscaling TRMM Monthly Precipitation Using Google Earth Engine and Google Cloud Computing." Remote Sensing 12, no. 23 (2020): 3860. http://dx.doi.org/10.3390/rs12233860.

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Accurate precipitation data at high spatiotemporal resolution are critical for land and water management at the basin scale. We proposed a downscaling framework for Tropical Rainfall Measuring Mission (TRMM) precipitation products through integrating Google Earth Engine (GEE) and Google Colaboratory (Colab). Three machine learning methods, including Gradient Boosting Regressor (GBR), Support Vector Regressor (SVR), and Artificial Neural Network (ANN) were compared in the framework. Three vegetation indices (Normalized Difference Vegetation Index, NDVI; Enhanced Vegetation Index, EVI; Leaf Area

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Irawan, Edi, Moh Khoridatul Huda, and Ratni Purwasih. "A learning trajectory for developing computational thinking in prospective mathematics teachers through Python programming in Google Colab." Alifmatika: Jurnal Pendidikan dan Pembelajaran Matematika 7, no. 1 (2025): 34–52. https://doi.org/10.35316/alifmatika.2025.v7i1.34-52.

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Computational thinking (CT) is a fundamental skill that needs to be developed by prospective mathematics teachers to improve problem-solving and logical reasoning. Integrating programming into mathematics learning is an effective approach to training this skill. This study aimed to design a hypothetical learning trajectory (HLT) for developing CT using Python programming on Google Colab. This study used a didactical design research (DDR) framework consisting of three stages: prospective analysis, metapedadidactic analysis, and retrospective analysis. The research participants were prospective

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Alfath Daryl Alhajir, Yisti Vita Via, and Wahyu Syaifullah Jauharis Saputra. "Sistem Pendeteksi Objek Beras Dan Benda Asing Berbasis Keras Dan Google Colab." Jurnal Informatika dan Sistem Informasi 2, no. 3 (2021): 580–86. http://dx.doi.org/10.33005/jifosi.v2i3.369.

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Standar SNI 6128:2020 menjelaskan kualitas beras menjadi 3 kelas berdasarkan komposisi dari komponen-komponen mutu beras, yaitu komponen mutu beras kepala, butir patah, butir menir, butir merah/hitam, butir rusak, butir kapur, benda asing, dan butir gabah, dimana beras kepala merupakan komponen mutu yang paling diinginkan dan sisanya tidak diinginkan. Oleh karena itu, dapat dilihat urgensi untuk membangun sistem yang dapat melakukan proses pemisahan beras tersebut dari komponen yang tidak diinginkan. Dikembangkan sebuah sistem berbasis deep learning yang dapat mendeteksi beras dan benda asing

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Mooers, Blaine. "Easing script writing on Google Colab with structural biology snippets." Acta Crystallographica Section A Foundations and Advances 78, a1 (2022): a175. http://dx.doi.org/10.1107/s2053273322098242.

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Gunawan, Teddy Surya, Arselan Ashraf, Bob Subhan Riza, et al. "Development of video-based emotion recognition using deep learning with Google Colab." TELKOMNIKA (Telecommunication Computing Electronics and Control) 18, no. 5 (2020): 2463. http://dx.doi.org/10.12928/telkomnika.v18i5.16717.

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Nazri, Siti Nur 'Ain, Kasypi Mokhtar, Anuar Abu Bakar, Benjamin Craig Mclellan, and Siti Marsila Mhd Ruslan. "Optimization berth allocation in container terminals: A Pyomo and Google Colab approach." Ocean & Coastal Management 258 (November 2024): 107359. http://dx.doi.org/10.1016/j.ocecoaman.2024.107359.

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Teddy, Surya Gunawan, Ashraf Arselan, Subhan Riza Bob, et al. "Development of video-based emotion recognition using deep learning with Google Colab." TELKOMNIKA Telecommunication, Computing, Electronics and Control 18, no. 5 (2020): 2463~2471. https://doi.org/10.12928/TELKOMNIKA.v18i5.16717.

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Emotion recognition using images, videos, or speech as input is considered as a hot topic in the field of research over some years. With the introduction of deep learning techniques, e.g., convolutional neural networks (CNN), applied in emotion recognition, has produced promising results. Human facial expressions are considered as critical components in understanding one's emotions. This paper sheds light on recognizing the emotions using deep learning techniques from the videos. The methodology of the recognition process, along with its description, is provided in this paper. Some of the

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GRADINARI, Oxana, Violeta BOGDANOVA, and Nicolai RUSSU. "Methodological recommendations for implementing an encryption algorithm using a codeword in Python." Acta et commentationes: Științe ale Educației 35, no. 1 (2024): 87–96. http://dx.doi.org/10.36120/2587-3636.v35i1.87-96.

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The article offers theoretical and practical material on encryption and decryption of text messages using a codeword cipher. Is shown an example of the implementation of the algorithm for cryptographic transformations of the specified cipher in the Python programming language. The development and execution of the Python program code was carried out in a free interactive cloud environment — Google Colab.

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Elsayed, Eman, and Doaa Fathy. "Semantic Deep Learning to Translate Dynamic Sign Language." International Journal of Intelligent Engineering and Systems 14, no. 1 (2021): 316–25. http://dx.doi.org/10.22266/ijies2021.0228.30.

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Dynamic Sign Language Recognition aims to recognize hand gestures of any person. Dynamic Sign Language Recognition systems have challenges in recognizing the semantic of hand gestures. These challenges come from the personal differences in hand signs from one person to another. Real-life video gesture frames couldn’t be treated as frame-level as a static sign. This research proposes a semantic translation system for dynamic hand gestures using deep learning and ontology. We used the proposed MSLO (Multi Sign Language Ontology) in the semantic translation step. Also, any user can retrain the sy

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