- DAY 1
- Brushing up Python basics.
- Understanding what is machine learning.
- Artificial Intelligence and Data Science.
- DAY 2 : In-depth learning about supervised, unsupervised,semi-supervised and reinforcement learning.
- DAY 3 : Learn about EDA (Exploratory Data Analysis) and Data Visualization.
- DAY 4 : Learn about Data Preperation(Data Cleaning and Preprocessing Steps (handling missing values, reducing to appropriate data type etc.))
- DAY 5 : Statistics for ML
- DAY 6 : Statistics for ML
- DAY 7 : Take dataset from here ,https://www.kaggle.com/c/titanic and start analyzing the problem and prepare your data.
- DAY 1 : Learn Linear regression.
- DAY 2 : Take dataset from here: https://www.kaggle.com/camnugent/california-housing-prices. Prepare your data and apply linear regression on it.
- DAY 3 : Learn Lasso and Ridge regression and explore other regressors.
- DAY 4 : Learn Evaluation Metrics for Regression and apply.
- DAY 5 : Learn Logistic regression.
- DAY 6 : Apply logistic regression on titanic problem.
- DAY 7 : Learn about various evaluation metrics for classification and apply.
- DAY 1 : Learn about various techniques to improve your model like handling categorical features, handling numerical data ,Feature engineering.
- DAY 2 : Learn about outliers and outlier handling.
- DAY 3 : Learn about hyperparameter tuning and apply.
- DAY 4 : Learn about various techniques to improve your model like handling categorical features, handling numerical data ,feature engineering.
- DAY 5 : Search for various other techniques to improve the performance.
- DAY 6 : Learn KNN ,decision tree , naive bayes, K means and apply to see the results
- DAY 7 : Learn about Ensemble models , Boosting algorithms and analyze.
- DAY 1 : Take https://www.kaggle.com/uciml/red-wine-quality-cortez-et-al-2009 dataset and understand the data and the problem statement.
- DAY 2 : Clean the data
- DAY 3 : Visualize and analyze the data
- DAY 4 : Apply algorithms learnt
- DAY 5 : Apply evaluation metrics
- DAY 6 : Improve the model
- DAY 7 : Improve the model and get the final model ready!!