## 15 Best Machine Learning Books for Beginners and Experts

This roundup post will help you find the perfect book to help you learn and understand Machine Learning and gain required hands-on practice.

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## 15 Best Machine Learning Books for Beginners and Experts

## Tensorflow CNN – How to build a great CNN model

## Neural Network Classification – Simple example

## TensorFlow Regression Model – Simple example

## Using the ARIMA model and Python for Time Series forecasting

## Simple Sklearn Ridge Regression Example In Python

## Popular Boosting Algorithms in Machine Learning

## Getting started with the Extra Trees algorithm in Python

This roundup post will help you find the perfect book to help you learn and understand Machine Learning and gain required hands-on practice.

This article covers the implementation of Convolutional Neural Network (CNN) for classifying grayscale and colored images using TensorFlow.

This tutorial covers how to use TensorFlow to build Neural Networks solving binary and multiclass classification problems.

This article describes how to use TensorFlow to build and tune a Neural Network model which will help you to solve a regression problem.

This article covers the basics of ARIMA model how to use the ARIMA model on a stationary and non-stationary time-series datasets.

This article describes how the Ridge and Lasso regressions work and how to apply them to solve regression problems using Python.

This article reviews popular Boosting algorithms in Machine Learning such as AdaBoost, Gradient Boosting, XGBoost, LighGBM, and CatBoost.

This article covers how the Extra Tree algorithm works shows how to use it to solve regression and classification problems using Python.