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Start with the big picture — what ML is, the three types (supervised, unsupervised, reinforcement), and how to prepare data. You'll learn feature selection and normalization using Indian retail data. By the end, you'll clean and transform a real dataset from Flipkart reviews.
Dive into the most common ML tasks — predicting numbers (regression) and categories (classification). You'll build models from scratch using gradient descent and evaluate them with real metrics. By the end, you'll predict Bengaluru house prices and classify spam messages.
Move from traditional ML to neural networks. Build an ANN for digit recognition, understand CNNs for images, and RNNs for sequences. Master classification metrics and model validation techniques. By the end, you'll design a neural network for a real problem.
Explore unsupervised learning — clustering and dimensionality reduction — and combine multiple models with ensemble methods. Build a recommendation system using matrix factorization. By the end, you'll segment customers and build a movie recommender like Netflix India.
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Saurav Singh
📌 All prices include 12% GST as per Indian tax regulations