MLJourney

Learning Calendar

Week 1: ML Foundations + Python

Day 1
What is ML?

Resource: Google ML Crash Course

Day 2
Python for Data Science

Resource: Kaggle Python Course

Day 3
EDA with Pandas/Seaborn

Resource: Kaggle Data Viz

Day 4
Data Cleaning

Resource: Kaggle Data Cleaning

Day 5
Feature Engineering

Resource: Kaggle Feature Eng.

Day 6
Linear Regression

Resource: StatQuest Video

Day 7
Project: House Price Prediction

Resource: Kaggle House Prices

Week 2: Core ML Algorithms

Day 8
Logistic Regression

Resource: StatQuest

Day 9
Decision Trees & RF

Resource: StatQuest

Day 10
Model Evaluation

Resource: Google MLCC Metrics

Day 11
Naive Bayes, KNN

Resource: Khan Academy

Day 12
Clustering: K-Means

Resource: YouTube Guide

Day 13
PCA for Dimensionality Reduction

Resource: StatQuest

Day 14
Project: Titanic Classification

Resource: Kaggle Titanic

Week 3: Advanced Concepts + Mini Projects

Day 15
Cross-Validation, GridSearchCV

Resource: Sklearn Docs

Day 16
Boosting & XGBoost

Resource: XGBoost Intro

Day 17
Intro to Neural Networks

Resource: 3Blue1Brown NN

Day 18
Deep Learning (Keras)

Resource: TensorFlow Intro

Day 19
CNN for Images

Resource: FreeCodeCamp DL

Day 20
NLP with Scikit-learn

Resource: Kaggle NLP

Day 21
Mini Project: Your Own ML Pipeline

Resource: Kaggle Datasets

Week 4: Kaggle, Deployment, Portfolio

Day 22
Intro to Kaggle Competitions

Resource: Kaggle Learn

Day 23
Learn from Kaggle Notebooks

Resource: Public notebooks

Day 24
Deployment Basics with Streamlit

Resource: Streamlit Docs

Day 25
Deploy ML App

Resource: Hugging Face or Render

Day 26
Resume, GitHub, Kaggle Polish

Resource: Add all projects

Day 27
Live Competition Submission

Resource: Kaggle Competitions

Day 28
Kaggle Forums, Networking

Resource: Comment, upvote, engage

Day 29
Revision Day

Resource: Practice weak spots

Day 30
Final Project + Submit + Deploy

Resource: End-to-End ML App