Machine Learning Roadmap
A practical, hands-on roadmap from fundamentals to production.
Vectors, matrices, eigenvalues, matrix operations
Probability distributions, Bayes theorem, hypothesis testing
Derivatives, gradients, chain rule, partial derivatives
Matrix Operations Library
beginnerBuild a Python library for basic matrix operations from scratch
- Python
- NumPy
Variables, data types, control flow, loops, functions
Lists, tuples, dictionaries, sets, comprehensions
Classes, inheritance, polymorphism, encapsulation
Reading/writing files, error handling, context managers
NumPy, Pandas, Matplotlib, Seaborn basics
Data Analysis Dashboard
beginnerAnalyze a dataset and create visualizations using Pandas and Matplotlib
- Python
- Pandas
- Matplotlib
Task Manager CLI
beginnerBuild a command-line task manager with file persistence
- Python
- JSON
Commits, staging, branches, merging, rebasing, resolving conflicts, remotes, pull requests, .gitignore
SELECT, WHERE, JOINs, GROUP BY, aggregates, subqueries, window functions, schemas, indexes, querying from Python
Shell navigation, files and permissions, pipes and redirection, environment variables, processes, SSH, shell scripting
UI components, layouts, state management
Building ML/data visualization apps
Stock Price Visualizer
beginnerCreate an interactive dashboard to visualize stock prices
- Streamlit
- Pandas
- yfinance
REST APIs, path operations, request/response models
Request validation, response models, custom validators
async/await, asynchronous endpoints, background tasks
SQLAlchemy, database connections, ORM basics
JWT tokens, OAuth2, API keys, security best practices
Containerization, Docker Compose, production deployment
RESTful Todo API
intermediateBuild a CRUD API with database integration
- FastAPI
- SQLAlchemy
- PostgreSQL
Authentication Service
intermediateCreate a user authentication API with JWT tokens
- FastAPI
- JWT
- OAuth2
Supervised vs Unsupervised learning, bias-variance tradeoff
Linear Regression, Ridge, Lasso, Polynomial Regression
Logistic Regression, Decision Trees, Random Forest, SVM, KNN
Feature scaling, encoding, selection, transformation
Accuracy, Precision, Recall, F1-Score, ROC-AUC, Confusion Matrix
K-fold, Stratified K-fold, Leave-One-Out
K-Means, DBSCAN, Hierarchical Clustering, PCA, t-SNE
Bagging, Boosting, XGBoost, LightGBM, CatBoost
GridSearchCV, RandomizedSearchCV, Optuna, Bayesian Optimization
L1/L2 Regularization, Dropout, Early Stopping
Manual labeling, Label Studio, Roboflow, active learning
House Price Prediction
beginnerPredict house prices using regression techniques
- Python
- Scikit-learn
- Pandas
Customer Churn Prediction
intermediateBuild a classification model to predict customer churn
- Python
- XGBoost
- Feature Engineering
Credit Card Fraud Detection
intermediateDetect fraudulent transactions using ensemble methods
- Python
- Imbalanced-learn
- LightGBM
Customer Segmentation
intermediateSegment customers using clustering algorithms
- Python
- K-Means
- PCA
Tokenization, stemming, lemmatization, stop words removal
Bag of Words, TF-IDF, N-grams
Word2Vec, GloVe, FastText
Sentiment Analysis, Text Classification, Named Entity Recognition
BLEU, ROUGE, Perplexity, F1-Score for NLP
Sentiment Analysis System
beginnerBuild a sentiment classifier for movie reviews
- Python
- NLTK
- Scikit-learn
Text Summarization Tool
intermediateCreate an extractive text summarization system
- Python
- spaCy
- TF-IDF
Spam Email Classifier
beginnerClassify emails as spam or not spam
- Python
- Bag of Words
- Naive Bayes
Perceptrons, activation functions, forward/backward propagation
Loss functions, optimizers (SGD, Adam, RMSprop), learning rate
Feedforward networks, multilayer perceptrons, backpropagation
Conv layers, pooling, image classification, transfer learning
RNN, LSTM, GRU, sequence modeling, time series
PyTorch, TensorFlow/Keras, model building & training
Object detection (YOLO, R-CNN), image segmentation, GANs
Dropout, batch normalization, data augmentation
Pre-trained models, fine-tuning, domain adaptation
Image Classifier
intermediateBuild an image classifier using CNN on CIFAR-10
- PyTorch
- CNN
- Transfer Learning
Object Detection System
advancedImplement YOLOv8 for real-time object detection
- PyTorch
- YOLO
- OpenCV
Handwritten Digit Recognition
beginnerBuild a digit recognizer using MNIST dataset
- TensorFlow
- CNN
- MNIST
Stock Price Predictor
intermediatePredict stock prices using LSTM networks
- PyTorch
- LSTM
- Time Series
Tensor creation, indexing, broadcasting, dtypes and devices, requires_grad, backward(), computation graphs
nn.Module and nn.Sequential, layers and parameters, custom forward(), state_dict, saving and loading models
Dataset and DataLoader classes, custom datasets, transforms and augmentation, batching, shuffling, num_workers
Loss functions and optimizers in torch, zero_grad/backward/step, train vs eval mode, validation loop, checkpointing, organizing code (Lightning)
CUDA devices, moving models/data to GPU, mixed precision (AMP), torch.compile, DataLoader tuning, DistributedDataParallel basics
ML lifecycle, CI/CD for ML, model versioning
MLflow, Weights & Biases, experiment management
Model versioning, staging, production deployment
- PLAYLISTMLOps PlaylistHINDI
- DOCMLflow - ML Model Registry· Model versioning, aliases and promotion to production
- CRSDataTalksClub - MLOps Zoomcamp Module 2: Experiment Tracking and Model Management· Lessons 2.4 Model Management and 2.5 Model Registry, with linked videos
- PLAYLISTDataTalksClub - MLOps Zoomcamp (video playlist)
REST APIs, model inference, batch vs real-time serving
Data drift, model drift, performance monitoring
Containerization, orchestration, scaling
AWS SageMaker, GCP AI Platform, Azure ML
Testing code, data and models, continuous integration and delivery pipelines, automated retraining and deployment gates, and release strategies like canary and shadow deploys.
ML Pipeline with MLflow
advancedBuild an end-to-end ML pipeline with experiment tracking
- MLflow
- Docker
- FastAPI
Model Deployment on AWS
advancedDeploy a trained model to AWS SageMaker
- AWS SageMaker
- Docker
- Python
Self-attention, multi-head attention, scaled dot-product
Encoder-decoder, positional encoding, layer normalization
BERT, RoBERTa, ALBERT, DeBERTa
GPT, GPT-2, GPT-3, autoregressive language modeling
BPE, WordPiece, SentencePiece, Unigram
Implement transformer architecture from ground up
Text Classification with BERT
intermediateFine-tune BERT for sentiment analysis
- Transformers
- BERT
- PyTorch
Question Answering System
advancedBuild a QA system using transformer models
- Transformers
- BERT
- Hugging Face
Mini GPT Implementation
advancedImplement a small-scale GPT model from scratch
- PyTorch
- Transformers
- Python
AI vs ML vs DL vs GenAI, generative models overview
Pre-training, supervised fine-tuning, RLHF basics
Zero-shot, few-shot, chain-of-thought, prompt optimization
BLEU, ROUGE, perplexity, human evaluation
Bias, hallucinations, responsible AI, alignment
OpenAI, Anthropic, Cohere, Groq integration
AI Content Generator
intermediateBuild a content generation tool using GPT API
- OpenAI API
- Python
- Streamlit
Prompt Engineering Playground
beginnerCreate a tool to test and compare different prompts
- OpenAI API
- Streamlit
- Python
Chains, agents, memory, callbacks
OpenAI, Ollama, Hugging Face, Groq in LangChain
Retrieval pipeline, embeddings, similarity search
FAISS, ChromaDB, Pinecone, Weaviate, Qdrant
sentence-transformers, OpenAI embeddings, custom embeddings
Multi-query retrieval, re-ranking, hybrid search
PDF parsing, text chunking, metadata extraction
PDF Q&A Chatbot
intermediateBuild a RAG system that answers questions from PDFs
- LangChain
- ChromaDB
- OpenAI
Documentation Assistant
advancedCreate an AI assistant for technical documentation
- LangChain
- Pinecone
- Streamlit
Knowledge Base Search
advancedBuild a semantic search engine for company knowledge
- LangChain
- Weaviate
- FastAPI
Agent loops, planning, tool use, memory
Reasoning + Acting, chain-of-thought for agents
Function calling, external APIs, code execution
Agent collaboration, communication protocols
State machines, graph-based agent workflows
Managing multiple agents, workflow optimization
Research Assistant Agent
advancedBuild an agent that conducts web research
- LangChain
- LangGraph
- OpenAI
Multi-Agent Task Solver
advancedCreate a system where multiple agents collaborate
- AutoGen
- CrewAI
- Python
Code Generation Agent
advancedBuild an agent that writes and executes code
- LangChain
- Code Interpreter
- OpenAI
Full fine-tuning vs transfer learning
Low-Rank Adaptation, quantized LoRA for efficient tuning
Prefix tuning, P-tuning, AdaLoRA, IA³
INT8, INT4, GPTQ, AWQ, GGML/GGUF
Pruning, knowledge distillation, QAT
Dataset preparation, instruction formatting
Reinforcement learning from human feedback overview
Fine-tune LLM with LoRA
advancedFine-tune a 7B model on custom dataset using LoRA
- PyTorch
- LoRA
- Hugging Face
Quantized Model Deployment
advancedQuantize and deploy an LLM for efficient inference
- GPTQ
- GGML
- FastAPI
Domain-Specific Chatbot
advancedFine-tune an LLM for a specific domain (legal, medical, etc.)
- LoRA
- Custom Dataset
- LangChain
Protocol for connecting AI to external data and tools
Building MCP servers, exposing tools and data
Integrating MCP with AI assistants and applications
Custom MCP Server
advancedBuild an MCP server for your own data sources
- MCP
- Python
- FastAPI
MCP-Powered Assistant
advancedCreate an AI assistant using MCP for tool access
- MCP
- LangChain
- Claude