Ebook TensorFlow in 1 Day Make your own Neural Network
Tensorflow is the most popular Deep Learning Library out there. It has fantastic graph computations feature which helps data scientist to visualize his designed neural network using TensorBoard. This Machine learning library supports both Convolution as well as Recurrent Neural network. It supports parallel processing on CPU as well as GPU. Prominent machine learning algorithms supported by TensorFlow are Deep Learning Classification, wipe & deep, Boston Tree amongst others. The book is very hands-on and gives you industry ready deep learning practices.
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Table of Contents
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- Chapter 1: What is Deep learning?
- Chapter 2: Machine Learning vs Deep Learning
- Chapter 3: What is TensorFlow?
- Chapter 4: Comparison of Deep Learning Libraries
- Chapter 5: How to Download and Install TensorFlow Windows and Mac
- Chapter 6: Jupyter Notebook Tutorial
- Chapter 7: Tensorflow on AWS
- Chapter 8: TensorFlow Basics: Tensor, Shape, Type, Graph, Sessions & Operators
- Chapter 9: Tensorboard: Graph Visualization with Example
- Chapter 10: NumPy
- Chapter 11: Pandas
- Chapter 12: Scikit-Learn
- Chapter 13: Linear Regression
- Chapter 14: Linear Regression Case Study
- Chapter 15: Linear Classifier in TensorFlow
- Chapter 16: Kernel Methods
- Chapter 17: TensorFlow ANN (Artificial Neural Network)
- Chapter 18: ConvNet(Convolutional Neural Network): TensorFlow Image Classification
- Chapter 19: Autoencoder with TensorFlow
- Chapter 20: RNN(Recurrent Neural Network) TensorFlow
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