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Programming With Python - 4 BOOK BUNDLE!!

Deep Learning with Keras

Here Is a Preview of What You’ll Learn Here...

• The difference between deep learning and machine learning
• Deep neural networks
• Convolutional neural networks
• Building deep learning models with Keras
• Multi-layer perceptron network models
• Activation functions
• Handwritten recognition using MNIST
• Solving multi-class classification problems
• Recurrent neural networks and sequence classification
• And much more...

Convolutional Neural Networks in Python

Here Is a Preview of What You’ll Learn In This Book...

• Convolutional neural networks structure
• How convolutional neural networks actually work
• Convolutional neural networks applications
• The importance of convolution operator
• Different convolutional neural networks layers and their importance
• Arrangement of spatial parameters
• How and when to use stride and zero-padding
• Method of parameter sharing
• Matrix multiplication and its importance
• Pooling and dense layers
• Introducing non-linearity relu activation function
• How to train your convolutional neural network models using backpropagation
• How and why to apply dropout
• CNN model training process
• How to build a convolutional neural network
• Generating predictions and calculating loss functions
• How to train and evaluate your MNIST classifier
• How to build a simple image classification CNN
• And much, much more!

Python Machine Learning

Here Is A Preview Of What You’ll Learn Here...

• Basics behind machine learning techniques
• Different machine learning algorithms
• Fundamental machine learning applications and their importance
• Getting started with machine learning in Python, installing and starting SciPy
• Loading data and importing different libraries
• Data summarization and data visualization
• Evaluation of machine learning models and making predictions
• Most commonly used machine learning algorithms, linear and logistic regression, decision trees support vector machines, k-nearest neighbors, random forests
• Solving multi-clasisfication problems
• Data visualization with Matplotlib and data transformation with Pandas and Scikit-learn
• Solving multi-label classification problems
• And much, much more...

Machine Learning With TensorFlow

Here Is a Preview of What You’ll Learn Here...

• What is machine learning
• Main uses and benefits of machine learning
• How to get started with TensorFlow, installing and loading data
• Data flow graphs and basic TensorFlow expressions
• How to define your data flow graphs and how to use TensorBoard for data visualization
• Main TensorFlow operations and building tensors
• How to perform data transformation using different techniques
• How to build high performance data pipelines using TensorFlow Dataset framework
• How to create TensorFlow iterators
• Creating MNIST classifiers with one-hot transformation

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