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vivekprajapati2048 / repository
In five courses, you will learn the foundations of Deep Learning, understand how to build neural networks, and learn how to lead successful machine learning projects. You will learn about Convolutional networks, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization, and more. You will work on case studies from healthcare, autonomous driving, sign language reading, music generation, and natural language processing. You will master not only the theory, but also see how it is applied in industry. You will practice all these ideas in Python and in TensorFlow, which we will teach.
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In five courses, you will learn the foundations of Deep Learning, understand how to build neural networks, and learn how to lead successful machine learning projects. You will learn about Convolutional networks, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization, and more. You will work on case studies from healthcare, autonomous driving, sign language reading, music generation, and natural language processing. You will master not only the theory, but also see how it is applied in industry. You will practice all these ideas in Python and in TensorFlow.
Selected from shared topics, language and repository description—not editorial ratings.
robertonetti /
This repository contains the practical exercises for the Computational Science course. It includes five Jupyter notebooks, each designed for a specific lesson, covering key topics in computational methods and scientific computing. Students will use these notebooks during the practical sessions to apply theoretical concepts to real-world problems.
27/100 healthM1shanyaaa /
A collection of Data Science labs for a KPI (КПІ) course, written in Jupyter Notebooks and covering five different lab assignments. The project contains code, data, and analysis scripts for hands‑on work with data science methods.
42/100 health