Mathew K AnalyticsPython For Machine Learning
A free 16-lesson course. Every lesson has a video walkthrough and a Jupyter notebook you can download or open in Google Colab. Tools covered: pandas, scikit-learn, NumPy, Matplotlib, SciPy, LightGBM.
14 minLesson 1
1 Capstone ML Project in Python: Build and Evaluate a Machine Learning Model
21 minLesson 3
Comprehensive Guide to Training Machine Learning Models with Scikit-Learn in Python
12 minLesson 4
2 Train-Test Split in Python: Step-by-Step Guide for Machine Learning Beginners
10 minLesson 5
3 Cross-Validation in Python: Machine Learning Model Evaluation Techniques
21 minLesson 7
Simple Linear Regression Model in Python with scikit-learn
11 minLesson 8
Polynomial Regression in Python: Complete Guide for Machine Learning Beginners
11 minLesson 14
Titanic Survival Prediction with Python: Data Analysis & Machine Learning Basics
13 minLesson 15
Building a Heart Disease Classification Model in Python: Step-by-Step Machine Learning Guide
12 minLesson 16
Handling Missing Values and Data Imputation Techniques in Python for Machine Learning
12 minLesson 18
Feature Scaling and Pipeline Construction in Python for Effective Machine Learning
15 minLesson 22
Understanding KMeans Clustering in Python: A Guide to Unsupervised Machine Learning
12 minLesson 23
Master DBSCAN & Hierarchical Clustering in Python for Unsupervised Learning
12 minLesson 26
Master Support Vector Machines (SVM) in Python for Advanced Machine Learning
9 minLesson 28
Understanding Gradient Boosting with LightGBM in Python for Advanced Machine Learning
15 minLesson 29
Master Ensemble Learning & Stacking Techniques in Python for Better Machine Learning Models
10 minLesson 30