Advanced Machine Learning Methods And Techniques

Learn Advanced Machine Learning Methods and Techniques for Data Analysis, Data Science, and Machine Learning

What you'll learn

Knowledge about Advanced Machine Learning methods, techniques, theory, best practices, and tasks

Deep hands-on knowledge of Advanced Machine Learning and know how to handle Machine Learning tasks with confidence

Advanced ensemble models such as the XGBoost models for prediction and classification

Detailed and deep Master knowledge of Regression, Regression analysis, Prediction, Classification, and Supervised Learning

Hands-on knowledge of Scikit-learn, Matplotlib, Seaborn, and some other Python libraries

Advanced knowledge of A.I. prediction/classification models and automatic model creation

Cloud computing: Use the Anaconda Cloud Notebook (Cloud-based Jupyter Notebook). Learn to use Cloud computing resources

And much more…

Requirements

The four ways of counting (+-*/)

Some Experience with Data Science, or Data Analysis, or Machine Learning

Python and preferably Pandas knowledge

Everyday experience using a computer with either Windows, MacOS, iOS, Android, ChromeOS, or Linux is recommended

Access to a computer with an internet connection

The course only uses costless software

Walk-you-through installation and setup videos for Cloud computing and Windows 10/11 is included

Description

Welcome to the course Advanced Machine Learning Methods and Techniques!Machine Learning is expanding and developing on a massive and global scale. Everywhere in society, there is a movement to implement and use Machine Learning Methods and Techniques to develop and optimize all aspects of our lives, businesses, societies, governments, and states.This course will teach you a useful selection of Advanced Machine Learning methods and techniques, which will give you an excellent foundation for Machine Learning jobs and studies. This course has exclusive content that will teach you many new things about Machine Learning methods and techniques.This is a two-in-one master class video course which will teach you to advanced Regression, Prediction, and Classification.You will learn advanced Regression, Regression analysis, Prediction and supervised learning. This course will teach you to use advanced feedforward neural networks and Decision tree regression ensemble models such as the XGBoost regression model.You will learn advanced Classification and supervised learning. You will learn to use advanced feedforward neural networks and Decision tree classifier ensembles such as the XGBoost Classifier model.You will learnKnowledge about Advanced Machine Learning methods, techniques, theory, best practices, and tasksDeep hands-on knowledge of Advanced Machine Learning and know how to handle Machine Learning tasks with confidenceAdvanced ensemble models such as the XGBoost models for prediction and classificationDetailed and deep Master knowledge of Regression, Regression analysis, Prediction, Classification, and Supervised LearningHands-on knowledge of Scikit-learn, Matplotlib, Seaborn, and some other Python librariesAdvanced knowledge of A.I. prediction/classification models and automatic model creationCloud computing: Use the Anaconda Cloud Notebook (Cloud-based Jupyter Notebook). Learn to use Cloud computing resourcesOption: To use the Anaconda Distribution (for Windows, Mac, Linux)Option: Use Python environment fundamentals with the Conda package management system and command line installing/updating of libraries and packages – golden nuggets to improve your quality of work lifeAnd much more…This course includesan easy-to-follow guide for using the Anaconda Cloud Notebook (Cloud-based Jupyter Notebook). You may learn to use Cloud Computing resources in this coursean easy-to-follow optional guide for downloading, installing, and setting up the Anaconda Distribution, which makes anyone able to install a Python Data Science environment useful for this course or for any Machine Learning or coding taska large collection of unique content, and this course will teach you many new things that only can be learned from this course on UdemyA compact course structure built on a proven and professional framework for learning.This course is an excellent way to learn advanced Regression, Prediction, and Classification! These are the most important and useful tools for modeling, AI, and forecasting.Is this course for you?This course is an excellent choice forAnyone who wants to learn Advanced Machine Learning Methods and TechniquesAnyone who wants to study at the University level and want to learn Advanced Machine Learning skills that they will have use for in their entire career!This course is the course we ourselves would want to be able to enroll in if we could time-travel and become new students. In our opinion, this course is the best course to learn Advanced Regression, Prediction, and classification.Course requirementsThe four ways of counting (+-*/)Some Experience with Data Science, Data Analysis, or Machine LearningPython and preferably Pandas knowledgeEveryday experience using a computer with either Windows, MacOS, iOS, Android, ChromeOS, or Linux is recommendedAccess to a computer with an internet connectionThe course only uses costless softwareWalk-you-through installation and setup videos for Cloud computing and Windows 10/11 is includedEnroll now to receive 10+ hours of video tutorials with manually edited English captions, and a certificate of completion after completing the course!

Overview

Section 1: Introduction

Lecture 1 Introduction

Lecture 2 Setup of the Anaconda Cloud Notebook

Lecture 3 Download and installation of the Anaconda Distribution (optional)

Lecture 4 The Conda Package Management System (optional)

Section 2: Advanced Models for Regression and Supervised Learning

Lecture 5 Overview

Lecture 6 Artificial Neural Networks, Feedforward Networks, and the Multi-Layer Perceptron

Lecture 7 Feedforward Multi-Layer Perceptrons for Prediction

Lecture 8 Decision Tree Regression model

Lecture 9 Random Forest Regression

Lecture 10 Voting Regression

Lecture 11 eXtreme Gradient Boosting Regression (XGBoost)

Section 3: Advanced Models for Classification and Supervised Learning

Lecture 12 Overview

Lecture 13 Artificial Neural Networks, Feedforward Networks, and the Multi-Layer Perceptron

Lecture 14 Feedforward Multi-Layer Perceptrons for Classification

Lecture 15 Decision Tree Classifier

Lecture 16 Random Forest Classifier

Lecture 17 Voting Classifier

Lecture 18 eXtreme Gradient Boosting Classifier (XGBoost)

Anyone who wants to learn Advanced Machine Learning Methods and Techniques,Anyone who wants to study at the University level and want to learn Advanced Machine Learning skills that they will have use for in their entire career!