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Machine Learning

A comprehensive, hands-on course taking you from statistics and probability all the way through supervised learning, unsupervised learning, model evaluation, and building end-to-end ML pipelines with Scikit-Learn.

⏱ 10 Weeks 📶 Intermediate 🌐 Online & Offline 🔔 Launching Soon
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Status
Coming Soon
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✔ 10 Weeks of Live Instruction
✔ Scikit-Learn & ML Projects
✔ Recorded Session Access
✔ Doubt Clearing Sessions
✔ Completion Certificate
Planned Curriculum

What This Course Will Cover

A sneak peek at what we're building for you.

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Statistics & Probability for Machine Learning
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Supervised Learning — Regression & Classification
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Unsupervised Learning — Clustering & Dimensionality Reduction
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Feature Engineering & Selection
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Model Evaluation — Cross-validation, Metrics & Bias-Variance
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Scikit-Learn — Pipelines, Transformers & Estimators
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Decision Trees, Random Forests & Gradient Boosting
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Support Vector Machines & k-Nearest Neighbours
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Hyperparameter Tuning — GridSearchCV & RandomizedSearch
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Introduction to Neural Networks with Keras
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ML Pipelines & Model Serialisation
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Capstone: End-to-end ML Project with Deployment

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