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🤖 Machine Learning Regression Algorithms from Scratch hero

Level: Intermediate

🤖 Machine Learning Regression Algorithms from Scratch

Learn linear, polynomial, ridge, lasso, and logistic regression using Python. Build predictive machine learning models, evaluate performance, and solve real-world regression problems.

4.0

2.4k+ learners

Duration

0 min

Learners

2.4k+ Enrolled Students

Session Recording

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Post Session

Mentor support

Session Schedule

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Includes

Expert Designed Curriculum

Doubt Clearing Session

Forever Community Access

After this course, you can

Clean and prepare datasets

Visualize data with Python

Build ML-ready datasets

Master Python for AI workflows

Course Curriculum

Expand or explore the full learning path.

Lessons

Start here after enrolling. These lessons form the core learning path for the course.

Supervised vs Unsupervised Learning

Train / Validation / Test Split

The Bias-Variance Tradeoff

Overfitting & Underfitting

Cross-Validation

Feature Scaling

Linear Regression (Revisited)

Polynomial Regression

Regularization (Ridge & Lasso)

Decision Tree Regression

Random Forest Regression

Gradient Boosting (XGBoost)

Logistic Regression

K-Nearest Neighbors (KNN)

Decision Trees & Random Forests (for Classification)

Support Vector Machines (SVM)

Naive Bayes

Gradient Boosting for Classification

What Unsupervised Learning Actually Solves

K-Means Clustering

Hierarchical Clustering

DBSCAN (Density-Based Clustering)

Principal Component Analysis (PCA)

Visualizing High Dimensions (t-SNE & UMAP)

Classification Metrics (Accuracy, Precision, Recall, F1)

Confusion Matrix, ROC & AUC

Regression Metrics (MAE, RMSE, R²)

Common Evaluation Pitfalls (Data Leakage & Friends)

Hyperparameter Tuning (Grid & Random Search)

Smarter Tuning (Bayesian Optimization)

Handling Imbalanced Data (SMOTE & Class Weights)

Missing & Messy Data

Feature Engineering & Selection

Building an ML Pipeline

The End-to-End ML Workflow

Deploying & Monitoring Your Model

Live Session Content

This topic will be taught live in an interactive session, allowing you to engage with the instructor and ask questions in real time. While recordings will be available, attending live offers the best learning experience.

Post Session Study Material

This section will be unlocked after the session. You'll get access to exclusive bonus content, additional examples, and on-demand resources to support continuous learning and deeper understanding.

Requirements

What you should have before starting the course.

Basic Python programming knowledge

No AI or ML experience required

A computer with Python installed

Willingness to work with real data

Tools you are going to use

PySpark

PySpark

Databricks

Databricks

Python

Python

SQL

SQL

Hadoop

Hadoop

Learn From Expert Instructor

Meet the mentors leading the live sessions.

Aarav Sharma

Aarav Sharma

Senior Frontend Engineer, StudioLabs

Aarav has mentored 1200+ learners and specializes in production UI systems and scalable frontend architecture.

LinkedIn
Ananya Mehta

Ananya Mehta

Design Technologist, CraftLabs

Ananya blends design and code to help learners ship portfolio-ready projects.

LinkedIn
Kabir Sayed

Kabir Sayed

Frontend Mentor, PixelWorks

Kabir focuses on clean code, accessibility, and practical frontend delivery.

LinkedIn

You should join this course if you

Students & Fresh Graduates

Build a strong portfolio

Learn from live mentors

Get feedback on your work

Working Professionals

Upgrade frontend skills

Ship real projects

Join a peer community

Career Switchers

Structured learning path

Hands-on practice

Guided sessions

Freelancers & Creators

Build client-ready sites

Improve delivery speed

Learn modern workflows

What you will get after completing this course

Completion certificate

Receive an official course completion certificate

Earn skill-focused feedback from mentors

Showcase your project in the Shattak community

Access lifetime notes and references

Stay connected with instructors for guidance

Completion bonus

Certificate access, community showcase, and lifetime mentor guidance.

Hear From Learners Who've Taken This Course

Honest feedback from learners who completed the live sessions.

4.8

24

Clear structure, solid examples, and a fast pace that keeps you engaged.

Riya Jain

Riya Jain

B.Tech, NIT Trichy

4.6

18

Practical sessions with feedback that helped improve my portfolio.

Kabir Singh

Kabir Singh

Frontend Intern, PixelWorks

4.9

12

Loved the structure and the live walkthroughs.

M

Meera Patel

Design Graduate

See what they have build

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Zainab Shaikh

Portfolio Landing Page

Portfolio Landing Page

300 Likes

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Devendra Singh

Product Marketing Site

Product Marketing Site

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Nadia Ahmed

Interactive Web Story

Interactive Web Story

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Get Life Time Access

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₹499

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Get Life Time Access

₹0

₹499

100% off