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Practice Machine Learning Programming Projects

Machine Learning is transforming industries across the globe. This Skill Tree presents a systematic approach to learning ML concepts and techniques. Designed for beginners, it provides a clear roadmap to understand algorithms, model training, and data analysis. Hands-on, non-video courses and practical exercises in an interactive ML playground ensure you develop real-world skills in building and deploying machine learning models.

Index Name Level Project Link
01 Deploying MobileNet With TensorFlow.js and Flask ★☆☆ 🚀 Start
02 Deploying a Simple TensorFlow Model ★☆☆ 🚀 Start
03 Classifying Iris Using SVM ★☆☆ 🚀 Start
04 Broad Listening Leads to Insight ★☆☆ 🚀 Start
05 Implementing Confusion Matrix for Classification ★☆☆ 🚀 Start
06 Data Cleaning and Purification with Python ★☆☆ 🚀 Start
07 Divide Dataset Into Mini-Batches ★☆☆ 🚀 Start
08 Early Stopping for Machine Learning ★☆☆ 🚀 Start
09 Encoding Label to One-Hot ★☆☆ 🚀 Start
10 Optimizing Gradient Descent for Global Optimization ★☆☆ 🚀 Start
11 K-Nearest Neighbors Regression Algorithm Implementation ★☆☆ 🚀 Start
12 Linear Regression Fitting and Plotting ★☆☆ 🚀 Start
13 Nonlinear Regression Model Estimation ★☆☆ 🚀 Start
14 Implementing Minkowski Distance Metric ★☆☆ 🚀 Start
15 Implementation of Polynomial Regression ★☆☆ 🚀 Start
16 Simple Handwritten Character Recognition Classifier ★☆☆ 🚀 Start
17 Balanced Batch Generation for Imbalanced Datasets ★☆☆ 🚀 Start

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