Sukhjot

Week 2 - day 6 Completed "Task B: Check the feature_importances_ attribute of your forest to see what truly drives the predictions" in ML League (1.5) on @OpenLearn_nitj! #Learning #Progress #OpenLearn

Week 2 - day 6 Completed "Task A: Train both a single Decision Tree and a Random Forest on the same dataset. Compare their performance on a "Test" set" in ML League (1.5) on @OpenLearn_nitj! #Learning #Progress #OpenLearn

Week 2 - day 5 Completed "Task B: Experiment with min_samples_split and observe how it affects the complexity of the tree" in ML League (1.5) on @OpenLearn_nitj! #Learning #Progress #OpenLearn

Week 2 - day 5 Completed "Task A: Train a Decision Tree and export the visualization as a PNG" in ML League (1.5) on @OpenLearn_nitj! #Learning #Progress #OpenLearn

Week 2 - day 5 Completed "Splitting Criteria: How the tree decides which feature to split on first", "Tree Depth" and "Visualization: Using plot_tree to see the logic of your model" in ML League (1.5) on @OpenLearn_nitj! #Learning #Progress #OpenLearn

Week 2 - day 4 Completed "Task B: Compare model accuracy on a dataset before and after using StandardScaler" in ML League (1.5) on @OpenLearn_nitj! #Learning #Progress #OpenLearn

Week 2 -day 4 Completed "Task A: Implement a basic KNN classifier from scratch using only NumPy (no Scikit-Learn)" in ML League (1.5) on @OpenLearn_nitj! #Learning #Progress #OpenLearn

Week 2 - day 4 Completed "Distance Math: Euclidean vs. Manhattan distance", "Choosing 'K': Impact of a small K (noise) vs. a large K (oversmoothing)" and "Scaling: Using StandardScaler to normalize features" in ML League (1.5) on @OpenLearn_nitj! #Learning #Progress #OpenLearn

Week 2 -day 3 Completed "Task A: Plot the Sigmoid function using Matplotlib." and "Task B: Train a Logistic Regression model on the Titanic dataset to predict survival" in ML League (1.5) on @OpenLearn_nitj! #Learning #Progress #OpenLearn

Week 2 - day 3 Completed "The Sigmoid Function", "Evaluation Metrics: Confusion Matrix, Precision, Recall, and the F1-Score" and "Thresholding: Deciding when a 0.6 probability counts as a "Yes."" in ML League (1.5) on @OpenLearn_nitj! #Learning #Progress #OpenLearn

Week 2 - day 2 Completed "Task B: Use Lasso on a dataset with 20 features and identify which features the model set to zero " in ML League (1.5) on @OpenLearn_nitj! #Learning #Progress #OpenLearn

Week 2 -day 2 Completed "Task A: Train a high-degree polynomial regression and observe the overfitting. Apply Ridge and see how the curve smooths out" in ML League (1.5) on @OpenLearn_nitj! #Learning #Progress #OpenLearn

Week 2 - day 2 Completed "L2 Regularization (Ridge)", "L1 Regularization (Lasso)" and "Elastic Net: The hybrid approach that combines L1 and L2 penalties" in ML League (1.5) on @OpenLearn_nitj! #Learning #Progress #OpenLearn

Week 2 - day 1 Completed "Task B: Train a Linear Regression model on a simple dataset (like square footage vs. house price) and plot the regression line" in ML League (1.5) on @OpenLearn_nitj! #Learning #Progress #OpenLearn

Week 2 - day 1 Completed "Task A: Use NumPy to manually calculate the MSE for a set of predictions versus actual values" in ML League (1.5) on @OpenLearn_nitj! #Learning #Progress #OpenLearn

Week 2 - day 1 Completed "The Hypothesis: y = mx + c (Simple) vs. Multiple", "Loss Functions: Understanding MSE and Mean Absolute Error (MAE)" and "Scikit-Learn: Using LinearRegression to fit and predict" in ML League (1.5) on @OpenLearn_nitj! #Learning #Progress #OpenLearn

Completed week 1 milestone task in ML League (1.5) on @OpenLearn_nitj! #Learning Built a reusable data preprocessing pipeline using Python | Pandas | NumPy | Matplotlib - Data cleaning - Feature engineering - Visualization - Stats with NumPy

Day 6 of ML league (1.5) 📚Completed "Task B: Create a Scatter plot showing the relationship between 'Fare' (ticket price) and 'Age' " in ML League (1.5) on @OpenLearn_nitj! #Learning #Progress #OpenLearn

Day 6 of ML league (1.5) 📚Completed "Task A: Using the Titanic data from Day 5, plot a histogram of passenger ages." in ML League (1.5) on @OpenLearn_nitj! #Learning #Progress #OpenLearn

Day 6 of ML league (1.5) 📚Completed "Basic Plots: Line, Scatter, Bar", "Distributions: Histograms" and "Subplots: Drawing multiple graphs at once" in ML League (1.5) on @OpenLearn_nitj! #Learning #Progress #OpenLearn