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Course Duration

Unlimited Duration


February 28, 2022

Frustrated with one-off blogs and too much math when trying to learn Machine Learning? Take the Next Step and Get Experienc-Based Playbooks that will Guide You to a Specific Result. Welcome to: Machine Learning Essentials (Phase II)
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Ernesto Lee
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Discover the process that you can use to get started and get good at applied machine learning for predictive modeling with the Python ecosystem including Pandas and scikit-learn. This book will lead you from a developer who is interested in machine learning with Python to a developer who has the resources and capability to work through a new dataset end-to-end using Python and develop accurate predictive models.

    • Intro to ML Agenda Unlimited
    • Introduction to Machine Learning Unlimited
    • Types of Machine Learning Unlimited
    • OPTIONAL TYPES OF ML Unlimited
    • DECK Unlimited
    • Hands on Intro to ML Lab Unlimited
    • Intro to ML Quiz 00:15:00
    • Programming Assignment 1 week, 3 days
    • What is Machine Learning? Unlimited
    • Intro to Machine Learning Quiz 00:05:00
    • Review Of Probability Unlimited
    • Probability Quiz 00:05:00
    • What is Supervised Learning? Unlimited
    • What is Unsupervised Learning? Unlimited
    • Classification Problems Unlimited
    • K – Nearest Neighbor Unlimited
    • Hands on K-Nearest Neighbor Unlimited
    • Coding Assignment – KNN Unlimited
    • Recommender System in Python Unlimited
    • Evaluating Classification Models Unlimited
    • Hyper Parameter Tuning and Model Fitting Unlimited
    • Supervised Learning Agenda Unlimited
    • Unit 2 Deck Unlimited
    • The Bias-Variance dilemma Unlimited
    • Regression Problems Unlimited
    • Linear Regression Unlimited
    • Hand on Linear Regression Unlimited
    • Coding Assignment – Linear Regression Unlimited
    • Evaluating Regression models Unlimited
    • Logistic Regression Unlimited
    • Module 2: Supervised Learning Quiz 00:05:00
    • Supervised Learning PDF Unlimited
    • Unsupervised Learning Agenda Unlimited
    • Introduction to Unsupervised Learning Unlimited
    • Clustering Unlimited
    • K – Means Clustering Unlimited
    • Hands on K-Means Clustering Unlimited
    • Hierarchical clustering methods Unlimited
    • Principal Component Analysis (PCA) Unlimited
    • Coding Assignment Unlimited
    • Module 3: Unsupervised Learning Quiz 00:05:00
    • Unsupervised Learning PDF Unlimited
    • Decision Trees Agenda Unlimited
    • Decision Trees Unlimited
    • Ensemble Learning Methods Unlimited
    • Random Decisions Forests Unlimited
    • Hands On Random Forest Unlimited
    • Gradient Boosting Machines Unlimited
    • Coding Assignment – Decision Trees Unlimited
    • Neural Networks Agenda Unlimited
    • Model and Feature Selection Unlimited
    • Loss functions and gradient Descent Unlimited
    • Artificial Neurons and Neural Networks Unlimited
    • Training neural networks and Backpropagation Unlimited
    • Pattern Recognition with Neural Networks Unlimited
    • Natural Language Processing (NLP) using Neural Networks Unlimited
    • Using NLP to build a Sentiment Analyzer Unlimited
    • Challenge Lab Unlimited
    • Review Of Models Unlimited
    • Capstone Project Unlimited
    • Review, Summary, And Capstone Agenda Unlimited
    • Machine Learning Essentials – Day One Unlimited
    • Machine Learning Essentials – Day Two Unlimited
    • Machine Learning Essentials – Day Three Unlimited
    • Machine Learning Essentials – Day Four Unlimited
    • Machine Learning Essentials – Day Five Unlimited
    • Machine Learning Essentials – Day Six Unlimited
    • Python Keywords Cheatsheet Unlimited
    • Python Data Structures Cheatsheet Unlimited
    • Python Complex Data Types Cheatsheet Unlimited
    • Python Classes Cheatsheet Unlimited
    • Python Functions Cheatsheet Unlimited
    • Common Python Code Challenges Unlimited
    • Final Project Details Unlimited
    • Resources Unlimited

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