English | MP4 | AVC 1280×720 | AAC 44KHz 2ch | 18 lectures (11h 15m) | 4.86 GB
Learn Advanced Machine Learning Methods and Techniques for Data Analysis, Data Science, and Machine Learning
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 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
- Option: 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 life
- And much more…
Table of Contents
Introduction
1 Introduction
2 Setup of the Anaconda Cloud Notebook
3 Download and installation of the Anaconda Distribution (optional)
4 The Conda Package Management System (optional)
Advanced Models for Regression and Supervised Learning
5 Overview
6 Artificial Neural Networks, Feedforward Networks, and the Multi-Layer Perceptron
7 Feedforward Multi-Layer Perceptrons for Prediction
8 Decision Tree Regression model
9 Random Forest Regression
10 Voting Regression
11 eXtreme Gradient Boosting Regression (XGBoost)
Advanced Models for Classification and Supervised Learning
12 Overview
13 Artificial Neural Networks, Feedforward Networks, and the Multi-Layer Perceptron
14 Feedforward Multi-Layer Perceptrons for Classification
15 Decision Tree Classifier
16 Random Forest Classifier
17 Voting Classifier
18 eXtreme Gradient Boosting Classifier (XGBoost)
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