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Python Machine Learning
Algorithm Design & Practical Code Execution
Richie Miller
If you want to discover how to use Python for Machine Learning, this book is for you!
This book will teach you how to pick the right tool for solving problems you just encountered! You will also discover how to solve a problem according to the data that you are using, based on different learning styles, characteristics or requirements using Python.
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In this book you will discover:
· Platforms and Libraries
· Regression & Linear Regression
· Polynomial Regression & Lasso Regression
· Ridge Regression & Perceptron Regression
· Classification Algorithms & Logistic Regression
· Naive Bayes & Support Vector Machines
· K Nearest Neighbors
· Decision Trees and Random Forests
· Neural Networks
· Convolutional Neural Networks
· Dimensionality Reduction & Linear Discriminant Analysis
· T Distributed Stochastic Neighbor Embedding
· Clustering Algorithms & K Means
· Gaussian Mixtures & Hierarchical Clustering
· Affinity Propagation & Other Machine Learning Algorithms
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