
Python Machine Learning
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.
GET THIS BOOK NOW AND START PROGRAMMING TODAY!
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
Duration - 1h 47m.
Author - Richie Miller.
Narrator - Google AI Mike.
Published Date - Saturday, 14 January 2023.
Copyright - © 2023 Szabolcs Juhasz ©.
Location:
United States
Description:
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. GET THIS BOOK NOW AND START PROGRAMMING TODAY! 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 Duration - 1h 47m. Author - Richie Miller. Narrator - Google AI Mike. Published Date - Saturday, 14 January 2023. Copyright - © 2023 Szabolcs Juhasz ©.
Language:
English
Opening Credits
Duración:00:00:09
Introduction
Duración:00:07:32
Chapter 1
Duración:00:05:56
Chapter 2
Duración:00:06:48
Chapter 3
Duración:00:10:12
Chapter 4
Duración:00:00:19
Chapter 5
Duración:00:00:45
Chapter 6
Duración:00:00:15
Chapter 7
Duración:00:04:48
Chapter 8
Duración:00:06:49
Chapter 9
Duración:00:05:56
Chapter 10
Duración:00:06:43
Chapter 11
Duración:00:08:53
Chapter 12
Duración:00:09:19
Chapter 13
Duración:00:03:26
Chapter 14
Duración:00:04:39
Chapter 15
Duración:00:06:04
Chapter 16
Duración:00:06:37
Chapter 17
Duración:00:08:42
Chapter 18
Duración:00:03:46