Google’s TensorFlow is an open-source and most popular deep learning library for research and production. This ebook covers basics to advance topics like linear regression, classifier, create, train and evaluate a neural network like CNN, RNN, auto encoders etc. Refer these machine learning tutorial, sequentially, one after the other, for maximum efficacy of learning.
Section 1- Introduction
- What is Deep learning? (First Chapter FREE)
- Machine Learning vs Deep Learning
- What is TensorFlow?
- Comparison of Deep Learning Libraries
- How to Download and Install TensorFlow Windows and Mac
- Jupyter Notebook Tutorial
- Tensorflow on AWS
- TensorFlow Basics: Tensor, Shape, Type, Graph, Sessions & Operators
Section 2- Advanced Stuff
- Tensorboard: Graph Visualization with Example
- Linear Regression
- Linear Regression Case Study
- Linear Classifier in TensorFlow
- Kernel Methods
- TensorFlow ANN (Artificial Neural Network)
- ConvNet(Convolutional Neural Network): TensorFlow Image Classification
- Autoencoder with TensorFlow
- RNN(Recurrent Neural Network) TensorFlow
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