1. Repository Structure
DSMP-2.0/
├── Week-1
│ ├── Python-Basics.ipynb
│ ├── Python-Data-Types.ipynb
│ ├── Python-Operators.ipynb
│ ├── Python-Control-Flow.ipynb
│ ├── Python-Strings.ipynb
│ ├── Time-Complexity.pdf
│ └── Week-1-Interview-Questions.pdf
├── Week-2
│ ├── Python-Lists.ipynb
│ ├── Python-Tuples.ipynb
│ ├── Python-Sets.ipynb
│ ├── Python-Dictionaries.ipynb
│ ├── Python-Functions.ipynb
│ └── Week-2-Interview-Questions.pdf
├── Week-3
│ ├── OOP-Part-1.ipynb
│ ├── OOP-Part-2.ipynb
│ ├── OOP-Part-3.ipynb
│ ├── Abstraction.ipynb
│ └── Week-3-Interview-Questions.pdf
├── Week-4
│ ├── File-Handling.ipynb
│ ├── Serialization-Deserialization.ipynb
│ ├── Exception-Handling.ipynb
│ ├── Decorators-Namespaces.ipynb
│ ├── Iterators-Generators.ipynb
│ └── Week-4-Interview-Questions.pdf
├── Week-5
│ ├── NumPy-Fundamentals.ipynb
│ ├── NumPy-Advanced.ipynb
│ └── Week-5-Interview-Questions.pdf
├── Week-6
│ ├── Pandas-Series.ipynb
│ ├── Pandas-DataFrames.ipynb
│ ├── Pandas-Important-Methods.ipynb
│ └── Week-6-Interview-Questions.pdf
├── Week-7
│ ├── Pandas-GroupBy.ipynb
│ ├── Pandas-Merging-Joining.ipynb
│ ├── Streamlit-Introduction.ipynb
│ ├── Case-Study-Indian-Startup-Funding.ipynb
│ └── Week-7-Interview-Questions.pdf
├── Week-8
│ ├── Matplotlib-Visualization.ipynb
│ ├── Seaborn-Visualization.ipynb
│ ├── Plotly-Introduction.ipynb
│ ├── Plotly-Graph-Objects.ipynb
│ ├── Plotly-Dash.ipynb
│ ├── COVID-19-Dashboard.ipynb
│ ├── Project-Plotly-Census-Data.ipynb
│ └── Week-8-Interview-Questions.pdf
├── Week-9
│ ├── Data-Gathering.ipynb
│ ├── Data-Assessing-Cleaning.ipynb
│ ├── ETL-AWS-RDS.ipynb
│ ├── Web-Scraping-Selenium.ipynb
│ └── Week-9-Interview-Questions.pdf
├── Week-10
│ ├── Database-Fundamentals.ipynb
│ ├── SQL-DDL.ipynb
│ ├── Tableau-Olympics-Dataset-Part-1.ipynb
│ └── Week-10-Interview-Questions.pdf
├── Week-11
│ ├── SQL-DML.ipynb
│ ├── SQL-Grouping-Sorting.ipynb
│ ├── Tableau-Part-2.ipynb
│ └── Week-11-Interview-Questions.pdf
├── Week-12
│ ├── SQL-Joins.ipynb
│ ├── SQL-Case-Study-Zomato.ipynb
│ ├── SQL-Subqueries.ipynb
│ ├── Flight-Dashboard-Python-SQL.ipynb
│ └── Week-12-Interview-Questions.pdf
├── Week-13
│ ├── SQL-Window-Functions.ipynb
│ ├── Data-Cleaning-SQL-Laptop.ipynb
│ ├── EDA-SQL-Laptop.ipynb
│ └── Week-13-Interview-Questions.pdf
├── Week-14
│ ├── Descriptive-Statistics-Part-1.ipynb
│ ├── Datetime-SQL.ipynb
│ └── Week-14-Interview-Questions.pdf
├── Week-15
│ ├── Descriptive-Statistics-Part-2.ipynb
│ ├── Probability-Distributions.ipynb
│ ├── SQL-Datetime-Case-Study-Flights.ipynb
│ ├── Database-Design.ipynb
│ └── Week-15-Interview-Questions.pdf
├── Week-16
│ ├── Normal-Distribution.ipynb
│ ├── Non-Gaussian-Probability-Distributions.ipynb
│ ├── Views-UDF-SQL.ipynb
│ ├── Transactions-Stored-Procedures.ipynb
│ └── Week-16-Interview-Questions.pdf
├── Week-17
│ ├── Central-Limit-Theorem.ipynb
│ ├── Central-Limit-Theorem-Proof.ipynb
│ ├── Confidence-Intervals.ipynb
│ └── Week-17-Interview-Questions.pdf
├── Week-18
│ ├── Hypothesis-Testing-Part-1.ipynb
│ ├── Hypothesis-Testing-Part-2.ipynb
│ ├── Chi-Square-Test.ipynb
│ ├── ANOVA.ipynb
│ └── Week-18-Interview-Questions.pdf
├── Week-19
│ ├── Tensors-Linear-Algebra-Part-1a.ipynb
│ ├── Vectors-Linear-Algebra-Part-1b.ipynb
│ ├── Matrices-Computation.ipynb
│ ├── Matrices-Intuition.ipynb
│ └── Week-19-Interview-Questions.pdf
├── Week-20
│ ├── Introduction-to-Machine-Learning.ipynb
│ ├── Simple-Linear-Regression.ipynb
│ ├── Multiple-Linear-Regression.ipynb
│ ├── Optimization-Big-Picture.ipynb
│ ├── Differential-Calculus.ipynb
│ └── Week-20-Interview-Questions.pdf
├── Week-21
│ ├── Gradient-Descent-Scratch.ipynb
│ ├── Batch-Gradient-Descent.ipynb
│ ├── Stochastic-Gradient-Descent.ipynb
│ ├── Mini-Batch-Gradient-Descent.ipynb
│ └── Week-21-Interview-Questions.pdf
├── Week-22
│ ├── Regression-Analysis-Part-1.ipynb
│ ├── Regression-Analysis-Part-2.ipynb
│ ├── Polynomial-Regression.ipynb
│ ├── Assumptions-of-Linear-Regression.ipynb
│ ├── Multicollinearity.ipynb
│ └── Week-22-Interview-Questions.pdf
├── Week-23
│ ├── Feature-Selection-Part-1.ipynb
│ ├── Feature-Selection-Part-2.ipynb
│ ├── Feature-Selection-Part-3.ipynb
│ └── Week-23-Interview-Questions.pdf
├── Week-24
│ ├── Regularization-Part-1.ipynb
│ ├── Ridge-Regression-Part-1.ipynb
│ ├── Ridge-Regression-Part-2.ipynb
│ ├── Ridge-Regression-Part-3.ipynb
│ ├── Ridge-Regression-Part-4.ipynb
│ ├── Lasso-Regression.ipynb
│ ├── Why-Lasso-Regression-Creates-Sparsity.ipynb
│ ├── ElasticNet-Regression.ipynb
│ └── Week-24-Interview-Questions.pdf
├── Week-25
│ ├── KNN-Part-1.ipynb
│ ├── KNN-Scratch.ipynb
│ ├── Decision-Boundary-Classification.ipynb
│ ├── Advanced-KNN-Part-2.ipynb
│ ├── Classification-Metrics-Part-1.ipynb
│ ├── Classification-Metrics-Part-2.ipynb
│ └── Week-25-Interview-Questions.pdf
├── Week-26
│ ├── Curse-of-Dimensionality.ipynb
│ ├── PCA-Part-1.ipynb
│ ├── PCA-Part-2.ipynb
│ ├── PCA-Part-3.ipynb
│ ├── Eigen-Vectors-Eigen-Values.ipynb
│ ├── Eigen-Decomposition-PCA-Variants.ipynb
│ ├── SVD.ipynb
│ └── Week-26-Interview-Questions.pdf
├── Week-27
│ ├── ROC-Curve.ipynb
│ ├── Cross-Validation.ipynb
│ ├── Data-Leakage.ipynb
│ ├── Hyperparameter-Tuning.ipynb
│ └── Week-27-Interview-Questions.pdf
├── Week-28
│ ├── Probability-Crash-Course-Part-1.ipynb
│ ├── Probability-Crash-Course-Part-2.ipynb
│ ├── Naive-Bayes-Part-1.ipynb
│ ├── Naive-Bayes-Part-2.ipynb
│ ├── Naive-Bayes-Part-3.ipynb
│ ├── Email-Spam-Classifier.ipynb
│ └── Week-28-Interview-Questions.pdf
├── Week-29
│ ├── Logistic-Regression-Part-1.ipynb
│ ├── Multiclass-Classification-Logistic-Regression.ipynb
│ ├── Maximum-Likelihood-Estimation.ipynb
│ ├── Logistic-Regression-Part-3.ipynb
│ └── Week-29-Interview-Questions.pdf
├── Week-30
│ ├── SVM-Part-1.ipynb
│ ├── SVM-Part-2.ipynb
│ ├── Constrained-Optimization-Problem.ipynb
│ ├── SVM-Dual-Problem.ipynb
│ ├── Maths-Behind-SVM-Kernels.ipynb
│ └── Week-30-Interview-Questions.pdf
├── Week-31
│ ├── Decision-Tree-Part-1.ipynb
│ ├── Decision-Tree-Part-2.ipynb
│ ├── Decision-Tree-Part-3.ipynb
│ ├── Decision-Tree-Visualization.ipynb
│ └── Week-31-Interview-Questions.pdf
├── Week-32
│ ├── Introduction-to-Ensemble-Learning.ipynb
│ ├── Bagging-Part-1.ipynb
│ ├── Bagging-Part-2.ipynb
│ ├── Bagging-Part-3.ipynb
│ ├── Random-Forest-Part-1.ipynb
│ ├── Random-Forest-Part-2.ipynb
│ └── Week-32-Interview-Questions.pdf
├── Week-33
│ ├── Gradient-Boosting-Part-1.ipynb
│ ├── Gradient-Boosting-Part-2.ipynb
│ ├── Gradient-Boosting-Part-3.ipynb
│ ├── Gradient-Boosting-Part-4.ipynb
│ ├── Gradient-Boosting-Part-5.ipynb
│ └── Week-33-Interview-Questions.pdf
├── Week-34
│ ├── XGBoost-Introduction.ipynb
│ ├── XGBoost-Regression.ipynb
│ ├── XGBoost-Classification.ipynb
│ ├── XGBoost-Complete-Math.ipynb
│ └── Week-34-Interview-Questions.pdf
├── Week-35
│ ├── Introduction-to-MLOps.ipynb
│ ├── Version-Control.ipynb
│ ├── ML-Reproducibility.ipynb
│ ├── Containerization.ipynb
│ ├── Deployment-Strategies.ipynb
│ └── Week-35-Interview-Questions.pdf
├── Week-36
│ ├── DAGs-in-MLOps.ipynb
│ ├── CI-CD.ipynb
│ ├── Monitoring-Alerting.ipynb
│ ├── Retraining-Rollback.ipynb
│ └── Week-36-Interview-Questions.pdf
├── Week-37
│ ├── Scaling-Efficiency-in-MLOps.ipynb
│ ├── ML-Technical-Debt.ipynb
│ └── Week-37-Interview-Questions.pdf
├── Week-38
│ ├── Encoding-Categorical-Features-1.ipynb
│ ├── Sklearn-ColumnTransformer-Pipeline.ipynb
│ ├── Sklearn-Deep-Dive.ipynb
│ ├── Encoding-Categorical-Features-2.ipynb
│ └── Week-38-Interview-Questions.pdf
├── Week-39
│ ├── Discretization-Part-1.ipynb
│ ├── Discretization-Part-2.ipynb
│ ├── Handling-Missing-Data-Part-1.ipynb
│ ├── Handling-Missing-Data-Part-2.ipynb
│ ├── Handling-Missing-Data-Part-3.ipynb
│ ├── Feature-Scaling.ipynb
│ └── Week-39-Interview-Questions.pdf
├── Week-40
│ ├── Outlier-Detection-Part-1.ipynb
│ ├── Outlier-Detection-Part-2.ipynb
│ ├── Outlier-Detection-Part-3.ipynb
│ ├── Feature-Transformation.ipynb
│ └── Week-40-Interview-Questions.pdf
├── Week-41
│ ├── KMeans-Clustering-Part-1.ipynb
│ ├── KMeans-Clustering-Part-2.ipynb
│ ├── KMeans-Clustering-Part-3.ipynb
│ ├── KMeans-Clustering-Scratch.ipynb
│ └── Week-41-Interview-Questions.pdf
├── Week-42
│ ├── DBSCAN.ipynb
│ ├── Hierarchical-Clustering.ipynb
│ ├── GMM-Part-1.ipynb
│ ├── GMM-Part-2.ipynb
│ ├── T-SNE-Part-1.ipynb
│ ├── T-SNE-Part-2.ipynb
│ └── Week-42-Interview-Questions.pdf
├── Week-43
│ ├── LDA.ipynb
│ ├── Apriori.ipynb
│ └── Week-43-Interview-Questions.pdf
├── Week-44
│ ├── Adaboost.ipynb
│ ├── Stacking.ipynb
│ ├── LightGBM-Part-1.ipynb
│ ├── LightGBM-Part-2.ipynb
│ ├── CatBoost-Part-1.ipynb
│ ├── Advanced-Hyperparameter-Tuning.ipynb
│ ├── Kaggle-Competition.ipynb
│ └── Week-44-Interview-Questions.pdf
├── Week-45
│ ├── NoSQL.ipynb
│ ├── Model-Explainability.ipynb
│ ├── FastAPI.ipynb
│ ├── AWS-Sagemaker.ipynb
│ ├── Handling-Imbalanced-Data.ipynb
│ └── Week-45-Interview-Questions.pdf
├── Capstone-Project
│ ├── Capstone-Project-Data-Gathering.ipynb
│ ├── Capstone-Project-Data-Cleaning.ipynb
│ ├── Capstone-Project-Feature-Engineering.ipynb
│ ├── Capstone-Project-EDA.ipynb
│ ├── Capstone-Project-Outlier-Detection-Removal.ipynb
│ ├── Capstone-Project-Missing-Value-Imputation.ipynb
│ ├── Capstone-Project-Feature-Selection.ipynb
│ ├── Capstone-Project-Model-Selection-Productionalization.ipynb
│ ├── Capstone-Project-Building-Analytics-Module.ipynb
│ ├── Capstone-Project-Building-Recommender-System.ipynb
│ ├── Capstone-Project-Building-Recommender-System-Part-2.ipynb
│ ├── Capstone-Project-Building-Insights-Module.ipynb
│ ├── Capstone-Project-Deploying-Application-AWS.ipynb
│ └── Week-46-Interview-Questions.pdf
└── resources
└── Project-Resources