Machine Learning Fundamentals

Machine Learning Fundamentals

English | MP4 | AVC 1920×1080 | AAC 44KHz 2ch | 21 Lessons (4h 5m) | 341 MB

Level Up Your Machine Learning Career. Master the ML Fundamentals Employers Crave.

Become a Machine Learning Expert. Launch Your Tech Career with LunarTech’s Proven Course – Trusted by Data Science Professionals.

You’ll learn

Fundamentals of Machine Learning
Build a solid foundation in ML concepts and terminology, enabling you to make informed decisions about your career path

Tackle Real-World Problems
Gain hands-on experience applying ML to solve practical challenges, building 6 portfolio projects that showcases your abilities.

Master In-Demand Techniques
Learn essential ML algorithms, giving you the flexibility to address different data challenges and impress potential employers.

Choose the Right Path
Develop the knowledge to select the right ML models and techniques, positioning you as a valuable problem-solver.

Table of Contents

1 Introduction
2 Machine Learning Basics
3 Bias-Variance Trade-off
4 Overfitting Regularization
5 Linear Regression – Causal Analysis (Part 1)
6 Linear Regression – (Part 2)
7 Logistic Regression & Maximum Likelihood Estimation (MLE)
8 Linear Discriminant Analysis (LDA)
9 K-Nearest Neighbors (KNN)
10 Decision Trees
11 Bagging
12 Random Forest
13 (Boosting Part 1) Introduction
14 Boosting (Part 2) – AdaBoost
15 Boosting (Part 3) – Gradient Boosting Model (GBM)
16 Boosting (Part 4) – XGBoost
17 Clustering (Part 1) – K-Means & Elbow Method
18 Clustering (Part 2) – Hierarchical Clustering
19 Clustering (Part 3) – DBScan
20 Dimensionality Reduction (Part 1) – Feature Selection
21 Dimensionality Reduction (Part 2) – Principal Component Analysis

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