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    Browsing by Subject Python (Computer program language)

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    • TVS.005210_TT_Basha, Niha Kamal_Bhatia Khan, Surbhi_Kumar, Abhishek_Mashat, Arwa__ Surbhi Bhatia Khan_ Abhishek KumarArwa Mashat - Deep Learning and I.pdf.jpg
    • Sách/Book

    • Deep learning and its applications using Python

      • Authors: - (2023)

    • This book thoroughly explains deep learning models and how to use Python programming to implement them in applications such as NLP, face detection, face recognition, face analysis, and virtual assistance (chatbot, machine translation, etc.). It provides hands-on guidance in using Python for implementing deep learning application models. It also identifies future research directions for deep learning
    • TVS.005250_TT_John Paul Mueller, Luca Massaron - Python for Data Science For Dummies, 3rd Edition-Wiley-Scrivener (2023).pdf.jpg
    • Sách/Book

    • Python for data science for dummies

      • Authors: Mueller, John Paul (2024)

    • Python for Data Science For Dummies lets you get your hands dirty with data using one of the top programming languages. This beginner's guide takes you step by step through getting started, performing data analysis, understanding datasets and example code, working with Google Colab, sampling data, and beyond. Coding your data analysis tasks will make your life easier, make you more in-demand as an employee, and open the door to valuable knowledge and insights.
    • TVS.005001_TT_(The Python Series) Stephen Lynch - Python for Scientific Computing and Artificial Intelligence-CRC Press (2023).pdf.jpg
    • Sách/Book

    • Python for scientific computation and artificial intelligence

      • Authors: Lynch, Stephen (2023)

    • This book was developed from a series of national and international workshops that the author has been delivering for over twenty years. The book is beginner friendly and has a strong practical emphasis on programming and computational modelling. Features: No prior experience of programming is required. Online GitHub repository available with codes for readers to practice. Covers applications and examples from biology, chemistry, computer science, data science, electrical and mechanical engineering, economics, mathematics, physics, statistics and binary oscillator computing. Full solutions to exercises are available as Jupyter notebooks on the Web"--