Bibliographies thématiques / Google Colab

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Littérature scientifique sur le sujet « Google Colab »

Auteur : Grafiati
Publié le 4 juin 2021
Mis à jour le 25 juillet 2025

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Articles de revues sur le sujet "Google Colab"

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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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Thèses sur le sujet "Google Colab"

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Giambi, Nico. "Sperimentazione di tecniche di Deep Learning per l'Object Detection." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2020. http://amslaurea.unibo.it/21557/.

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Il lavoro svolto in questa tesi ruota intorno alla sperimentazione di tecniche di Deep Learning per l'Object Detection, ovvero la costruzione di un Object Detector a la YOLO partendo da zero testando per ogni parte della costruzione più alternative possibili per verificarne la praticità e correttezza, estrapolando per le varie fasi le soluzioni migliori, sia dal punto di vista funzionale sia per quanto riguarda la semplicità. In questa tesi è stato creato un Object Detector sfruttando MobileNet (una Convolutional Neural Network molto veloce) associata ad un algoritmo in stile YOLO (principalme
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Gunn-Graffy, Colin. "When in Rome, Beijing or Brussels: Cultural Considerations of International Business Communication." Thesis, Boston College, 2007. http://hdl.handle.net/2345/565.

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Thesis advisor: Donald Fishman<br>This thesis examines the role of culture in international business communication through case studies of several multinational corporations. The first case looks at Coca-Cola's product recall crisis in Belgium in 1999, which exhibited an uncharacteristic deviation from the company's well-known brand marketing brilliance. The second case deals with problems that Disney encountered as it tried to establish its first theme park in Europe in the 1990s and found itself facing a culture as proud and protective as Disney itself. At the heart of these cases were outda
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Livres sur le sujet "Google Colab"

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Paper, David. State-Of-the-Art Deep Learning Models in TensorFlow: Modern Machine Learning in the Google Colab Ecosystem. Apress L. P., 2021.

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Castillo Catalán, María Isabel, Iker Martín Álvarez, and Vicente R. Tomás. Introducción al uso de Google Collab [Vídeo]. Universitat Jaume I, 2023. http://dx.doi.org/10.6035/adp2024.3.

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Chapitres de livres sur le sujet "Google Colab"

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Lynch, Stephen. "Jupyter Notebooks and Google Colab." In Python for Scientific Computing and Artificial Intelligence. Chapman and Hall/CRC, 2023. http://dx.doi.org/10.1201/9781003285816-3.

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Lynch, Stephen. "Google Colab, SymPy and GitHub." In A Simple Introduction to Python. Chapman and Hall/CRC, 2024. http://dx.doi.org/10.1201/9781003472759-5.

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Paper, David. "Build Your First Neural Network with Google Colab." In TensorFlow 2.x in the Colaboratory Cloud. Apress, 2021. http://dx.doi.org/10.1007/978-1-4842-6649-6_2.

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Shariar, Sarjil, and K. M. Azharul Hasan. "Parallel Computation of Hadamard Product for Dynamic Dataset on Google Colab." In ICT with Intelligent Applications. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-4177-0_48.

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Maczuga, Paweł, Maciej Sikora, Tomasz Służalec, et al. "Physics Informed Neural Network Code for 2D Transient Problems (PINN-2DT) Compatible with Google Colab." In Lecture Notes in Computer Science. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-97629-2_13.

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Cervera, Enric, Raúl Marín, and Josep Marín. "Más allá de Jupyter: usando Google Colab para la programación de robots." In XLIII Jornadas de Automática: libro de actas: 7, 8 y 9 de septiembre de 2022, Logroño (La Rioja), 2022nd ed. Servizo de Publicacións da UDC, 2022. http://dx.doi.org/10.17979/spudc.9788497498418.0662.

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En los últimos años el entorno interactivo de programación Jupyter se ha popularizado enormemente como herramienta para la enseñanza en muchos campos científicos y técnicos, incluyendo la robótica. Jupyter permite integrar materiales documentales con ejemplos de código ejecutables y modificables. En este trabajo proponemos el uso de Google Colab, una herramienta basada en Jupyter, para mejorar la experiencia del usuario y programador, tanto del profesor que prepara el material como del estudiante que lo usa. Estas mejoras se basan principalmente en la integración de Google Drive y GitHub, lo q
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Nogueira, Rodrigo Ramos, Nader Ghoddosi, and Pedro Sidnei Zanchett. "Using Google Colaboratory as an online tool to support teaching and learning processes in information technology in Brazilian Distance Learning Courses." In Transformación digital en la educación: innovaciones y desafíos en la tecnología educativa. United Academic Journals (UA Journals), 2024. https://doi.org/10.54988/uaj.000028.007.

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The demand for Information Technology (IT) distance education has experienced a significant increase, growing by 70% since 2020. This growth is particularly notable in fields such as programming and cybersecurity, which are projected to continue expanding by an additional 11% by 2029. In response to this trend, Google Colaboratory, a free and advanced coding environment, has emerged as a valuable tool for educators and students alike. This paper proposes a methodology that leverages the interactive capabilities of Google Colab to enhance the teaching of programming. By creating tailored notebo
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Kandan, M., D. Srinivasarao, M. Kalyan Chakravarthi, S. Gnana Prasanna, David Raul Hurtado Tiza, and Mohit Tiwari. "The Impact of Cloud Computing on Organisational Agility and Competitive Advantage in Management Information Systems." In Advances in Computational Intelligence and Robotics. IGI Global, 2024. https://doi.org/10.4018/979-8-3373-1032-9.ch022.

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In the context of management information systems (MIS), this study investigates the transformational impact of cloud computing on organizational agility and competitive advantage. This research gathered, processed, alongside analysed data from various sources by utilizing the capabilities of Google Colab. We revealed insights into the significant impacts of cloud adoption on MIS performance using text mining, sentiment analysis, statistical testing, including machine learning. Scalability, quick deployment, cost-effectiveness, and global reach are highlighted as important factors in organizati
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Comlan, Maurice, and Manuela Alokpo. "Classification of Gestational Diabetes Using Machine Learning Techniques." In Advances in Transdisciplinary Engineering. IOS Press, 2023. http://dx.doi.org/10.3233/atde231066.

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In this work, we characterized the association of diabetes with pregnancy and developed a classification system for gestational diabetes based on machine learning models. Using statistical data, we can predict whether or not a patient has gestational diabetes based on certain attributes: age, number of pregnancies, insulin levels, etc. This allows the patient to seek medical attention quickly to reduce the risk of complications from this disease on her health. To achieve this goal, we proposed a method of data classification using supervised learning techniques: KNN, decision tree, and Random
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Rama, Olsa. "Analyzing Billionaire Databases Using Python." In Advances in Systems Analysis, Software Engineering, and High Performance Computing. IGI Global, 2023. http://dx.doi.org/10.4018/978-1-6684-9809-5.ch002.

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The network of billionaires could be analyzed through their data and information. Python has the capability of taking data and information from many sources and analyzing them from a single database. The idea of the report is to compare databases with all the billionaires in the world at different time frames. By collecting all the needed, such as personal information and integrable data, the program will output them in a table. The program takes datasets in the Comma Separated Values file and gives out the output through the Google Colab platform. The authors give importance to net worth and
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Actes de conférences sur le sujet "Google Colab"

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Cartusiano, Romnick U., and Jennifer C. Dela Cruz. "Comparative Evaluation for Classification of WBC Sub-Particles Using Google Colab GPU/TPUs." In 2024 8th International Conference on Electrical, Telecommunication and Computer Engineering (ELTICOM). IEEE, 2024. https://doi.org/10.1109/elticom64085.2024.10865131.

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N, Lavanya B., Anitha Rathnam K. V, Abhishek Appaji, Kiran K, P. Deepa Shenoy, and Venugopal K. R. "Leveraging LLM GPT-3.5 for Sentiment Analysis: A Comparative Study Across PC and Google Colab." In 2024 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT). IEEE, 2024. http://dx.doi.org/10.1109/conecct62155.2024.10677300.

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Mandal, Pallab, Swaroop Srisailam, Praveen Pankajakshan, and Kumar Rajamani. "A Comparative Study of Spatio-Temporal Segmentation Performance: AWS g4dn.xlarge vs. Google Colab T4 GPU." In 2024 IEEE 31st International Conference on High Performance Computing, Data and Analytics Workshop (HiPCW). IEEE, 2024. https://doi.org/10.1109/hipcw63042.2024.00054.

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Ferreira, Ricardo, Michael Canesche, and Jerônimo Penha. "Google Colab para Ensino de Computação." In Anais Estendidos do Simpósio Brasileiro de Educação em Computação. Sociedade Brasileira de Computação, 2023. http://dx.doi.org/10.5753/educomp_estendido.2023.228279.

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Este minicurso teórico-prático tem como objetivo a introdução ao uso do Google Colab como uma ferramenta de ensino à distância e/ou atividades práticas síncronas ou assíncronas em aula presencial ou remotas na Educação em Computação. Tradicionalmente, o Google Colab vem sendo usado no ensino de inteligência artificial e aprendizado de máquina. O minicurso irá apresentar aos participantes vários exemplos, ideias e metodologias para uso em qualquer disciplina. Mostrando como usar outras linguagens além de Python, como inserir outras ferramentas de ensino, criação de comandos mágicos para simplif
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Potluri, Tarun, Yong Shi, Hossain Shahriar, et al. "Secure Software Development in Google Colab." In 2023 IEEE World AI IoT Congress (AIIoT). IEEE, 2023. http://dx.doi.org/10.1109/aiiot58121.2023.10174336.

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Edwards, Katlyn, Corrie Scalisi, Julianne DeMars-Smith, and Key Lee. "Google Colab for Teaching CS and ML." In SIGCSE 2024: The 55th ACM Technical Symposium on Computer Science Education. ACM, 2024. http://dx.doi.org/10.1145/3626253.3635432.

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Ferreira, Ricardo, Michael Canesche, and José Nacif. "Ideias para uso do Google Colab no Ensino de Computação." In Anais Estendidos do Simpósio Brasileiro de Educação em Computação. Sociedade Brasileira de Computação, 2023. http://dx.doi.org/10.5753/educomp_estendido.2023.229073.

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O Google Colab vem sendo amplamente utilizado pela comunidade de programadores. Porém, a maior parte dos usuários fazem uso de laboratórios para ensino e pesquisa nos domínios de aprendizado de máquina e inteligência artificial. Este trabalho traz novas ideias para explorar a grande diversidade de recursos que o Colab pode oferecer mas são poucos explorados. Através do uso do próprio Colab criamos uma série de atividades para a comunidade docente desenvolver laboratórios de aula. Além de Python, mostraremos que outras linguagens podem ser incluídas, assim como é possível instalar ferramentas d
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Sabino, Carlos Eduardo, José A. M. Nacif, and Ricardo Ferreira. "Acesso Compartilhado à Recursos Físicos com Google Colab." In Anais Estendidos do Simpósio Brasileiro de Educação em Computação. Sociedade Brasileira de Computação, 2024. http://dx.doi.org/10.5753/educomp_estendido.2024.238794.

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Este trabalho apresenta uma proposta para proporcionar aos alunos acesso a recursos de hardware para execução de projetos, mesmo em contextos onde a disponibilidade de tais recursos é limitada. Apresentamos um ambiente virtual de programação utilizando o Google Colab. Os alunos podem submeter seus códigos para execução em um recurso de hardware compartilhado, permitindo-lhes observar a execução em tempo real em um ambiente físico real e tangível. Esta abordagem não apenas facilita o acesso a recursos físicos com disponibilidade limitada, como reduz custos e motiva os estudantes com a visualiza
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Freitas, Isabela, Pedro Coura, José Augusto Nacif, and Ricardo Ferreira. "Programação de Jogos com Google Colab e Chatgpt." In Anais Estendidos do Simpósio Brasileiro de Educação em Computação. Sociedade Brasileira de Computação, 2025. https://doi.org/10.5753/educomp_estendido.2025.6576.

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Суманеева, Анастасия Васильевна, and Ахмед Алипашевич Мамедов. "DIGITIZATION OF A. V. VAMPILOV'S ARTISTIC WORK: CREATING A DICTIONARY OF THE PLAYWRIGHT'S PLAYS." In Перспективное научно-техническое развитие: тенденции, проблемы и пути совершенствования: сборник статей международной научной конференции (Санкт-Петербург, Апрель 2025). Crossref, 2025. https://doi.org/10.58351/250417.2025.38.27.002.

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В статье представлен опыт создания электронного авторского словаря-конкорданса на материале пьесы А. В. Вампилова «Прощание в июне» с применением языка программирования Python в облачной среде Google Colab The article presents the experience of creating an electronic author’s dictionary-concordance based on the material A. V. Vampilov’s play “Farewell in June” using the Python programming language in the Google Colab platform
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