No Black Box Machine Learning Course – Learn Without Libraries

Gain a deep understanding of machine learning systems by coding without relying on libraries in this comprehensive JavaScript course. Demystify the inner workings of machine learning while enhancing your software development skills. Create a drawing app, work with data, build a data visualizer, and implement feature extraction techniques. Learn to create scatter plots and custom charts for data visualization. Explore classification algorithms including Nearest Neighbor and K Nearest Neighbors. Dive into model evaluation, decision boundaries, and compare your implementations with Python and scikit-learn. Complete hands-on assignments and projects to reinforce your learning. Suitable for those with basic programming knowledge and some understanding of linear algebra, trigonometry, and interpolation.

CHART TUTORIAL mentioned at : https://youtu.be/n8uCt1TSGKE
⌨️ Introduction
⌨️ Drawing App
⌨️ Homework 1
⌨️ Working with Data
⌨️ Data Visualizer
⌨️ Homework 2
⌨️ Feature Extraction
⌨️ Scatter Plot
⌨️ Custom Chart
⌨️ Homework 3
⌨️ Nearest Neighbor Classifier
⌨️ Homework 4 better box
⌨️ Data Scaling
⌨️ Homework 5
⌨️ K Nearest Neighbors Classifier
⌨️ Homework 6
⌨️ Model Evaluation
⌨️ Homework 7
⌨️ Decision Boundaries
⌨️ Homework 8
⌨️ Python & SkLearn
⌨️ Homework 9