AI & ML Learning Paths
🚀 AI & Machine Learning Learning Paths
Step 1: Foundations
Mathematics
Linear Algebra basics (vectors, matrices)
Probability & Statistics fundamentals
Basic Calculus (derivatives, gradients)
Programming
Learn Python (syntax, data structures)
Practice with libraries: NumPy, Pandas, Matplotlib
Step 2: Basic Machine Learning
Understand types of ML: supervised, unsupervised, reinforcement learning
Study core algorithms:
Linear Regression
Logistic Regression
Decision Trees
K-Nearest Neighbors (KNN)
Learn data preprocessing:
Handling missing data
Feature scaling and encoding
Explore evaluation metrics (accuracy, precision, recall)
Step 3: Intermediate Machine Learning
Learn ensemble methods:
Random Forest
Gradient Boosting (XGBoost, LightGBM)
Understand clustering (K-Means, DBSCAN)
Study dimensionality reduction (PCA, t-SNE)
Practice on real datasets (Kaggle competitions or open datasets)
Step 4: Deep Learning
Learn basics of Neural Networks
Study key architectures:
Convolutional Neural Networks (CNNs) for images
Recurrent Neural Networks (RNNs) for sequences
Use deep learning frameworks:
TensorFlow or PyTorch
Work on projects like image classification, text generation
Step 5: Advanced AI Topics
Explore Natural Language Processing (NLP)
Study Reinforcement Learning
Learn about Generative Models (GANs, VAEs)
Dive into Transformers and Large Language Models
Step 6: Practical Applications & Deployment
Learn model optimization and tuning (hyperparameter tuning)
Study model deployment basics (APIs, cloud platforms)
Understand ethics and fairness in AI
Build end-to-end AI applications
📚 Recommended Resources
Courses:
Coursera (Andrew Ng’s ML and DL courses)
fast.ai Deep Learning course
Udacity AI Nanodegree
Books:
“Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow” by Aurélien Géron
“Deep Learning” by Ian Goodfellow
Practice Platforms:
Kaggle
Google Colab (for coding practice)
🔑 Tips for Success
Work on projects as you learn.
Participate in competitions or contribute to open-source.
Join communities (forums, Discord, Reddit) for support.
Stay updated with the latest research and trends.
Learn AI ML Course in Hyderabad
Read More
What Are the Prerequisites for Learning Machine Learning?
The Journey from Basic Algorithms to Complex AI Models
Basic Principles of Clustering in Machine Learning
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