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25 Key Machine Learning Algorithms - Math, Intuition, Python

25 Key Machine Learning Algorithms - Math, Intuition, Python

25 Key Machine Learning Algorithms - Math, Intuition, Python - 
Learn the core ML algorithms with clear math, intuitive explanations, and Python implementation.

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Description
Do you want to understand machine learning algorithms and how artificial intelligence works but don’t know where to start? Or perhaps you already have some knowledge and want to deepen your understanding of AI-driven algorithms?

- This course is exactly what you need!



In this course, you’ll master 25 key machine learning algorithms:

Simple Linear Regression

Multiple Linear Regression

Logistic Regression

Decision Trees

K-means

Model Evaluation

Naive Bayes

Ridge Regression

Bagging

Random Forest

Boosting

LASSO

KNN

Gradient Boosting

PCA - Principal Component Analysis

XGBoost

LDA - Linear discriminant analysis

QDA - Quadratic discriminant analysis

Agglomerative Hierarchical Clustering

Hard-Margin SVM

SVM

DBSCAN

t-SNE

Isolation Forest

Perceptron



Each lesson is designed to provide clear, structured learning with three essential components:

Theory – A deep dive into the mathematical concepts behind each algorithm

Examples – Simple scenarios to illustrate how each algorithm works

Implementation – Step-by-step Python coding to bring each algorithm to life



Why This Course Stands Out:

No long videos – Just focused learning! This course is perfect for those who prefer reading over passive video watching.

Math made simple – Algorithms are explained in an accessible way, with intuitive examples to help you understand their logic.

Hands-on coding – You’ll implement every algorithm from scratch, ensuring you truly understand the process.



Ready to start your journey in Machine Learning?

Who this course is for:
  • Aspiring Data Scientists and Machine Learning Engineers
  • Beginners in Machine Learning who don’t know where to start
  • Those looking for a balance between simple explanations and mathematical formalism
  • People who prefer reading and analyzing rather than watching long lectures

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