Basics-Of-Data-Science-Practise , Practising developer's guide to introduction to Data science (nvidia pdf) and some notes for me
Roadmap for learning : NumPy Basics:
Start with basic NumPy operations such as array creation, indexing, slicing, and basic mathematical operations.
Learn about array manipulation, reshaping, and stacking.
Understand broadcasting and how it simplifies array operations.
NumPy Advanced Topics:
Dive deeper into advanced array manipulation techniques like fancy indexing and boolean indexing.
Explore universal functions (ufuncs) and their applications.
Learn about structured arrays and record arrays for handling structured data.
Introduction to TensorFlow:
Begin with installing TensorFlow in a Colab notebook and importing necessary libraries.
Learn about tensors, the fundamental data structure in TensorFlow, and how they differ from NumPy arrays.
Explore TensorFlow operations (ops) for basic arithmetic, matrix operations, and more.
Building Neural Networks with TensorFlow:
Start with simple feedforward neural networks (also known as dense or fully connected networks) using TensorFlow's high-level API, Keras.
Understand the basic components of neural networks such as layers, activation functions, and loss functions.
Train your first neural network on a simple dataset and evaluate its performance.
Intermediate TensorFlow Concepts:
Dive deeper into TensorFlow's API and learn about more complex neural network architectures like convolutional neural networks (CNNs) and recurrent neural networks (RNNs).
Explore advanced optimization techniques, regularization methods, and hyperparameter tuning to improve model performance.
Learn how to handle real-world data with TensorFlow's data preprocessing utilities.
Advanced Topics and Applications:
Explore advanced TensorFlow topics such as transfer learning, custom layers, and custom training loops.
Dive into specific applications of deep learning such as natural language processing (NLP), computer vision, and reinforcement learning.
Work on hands-on projects or participate in Kaggle competitions to apply your skills to real-world problems.