About Phase 1 In Phase 1 of the DeepLearning Cohort 2023, we will be taking our Python skills from beginner to advanced levels. This phase aims to provide a strong foundation in Python programming and equip us with the necessary skills to work with frameworks like TensorFlow and understand their code. Additionally, we will learn how to build custom classes whenever required, enabling us to develop more sophisticated deep-learning models and applications.
In Phase 1, we will cover the following topics:
Learning Python from the basics to an advanced level, including topics like functions, classes, and modules.
Exploring essential data science libraries such as NumPy, Pandas, Matplotlib, and Seaborn. These libraries are crucial for data manipulation, visualization, and analysis.
Understanding the fundamentals of TensorFlow, a popular deep learning framework, and learning how to create and train basic neural networks.
This repository will contain the code and examples for each topic covered in Phase 1. You can find the code, notebooks, and other learning materials in their respective directories. Let's Get Started! Let's dive into the exciting world of Python and Data Science! We hope this journey in Phase 1 will prepare us for more advanced deep learning concepts in subsequent phases.
Happy learning and coding!
Click Below to open 1.intro_python.ipynb in google Colab
