1 Welcome to the course! (33.52 MB)
2 Installing Anaconda (39.75 MB)
3 Exploring Jupyter Notebook (24.7 MB)
4 Let's Try Some Coding Together in Jupyter Note Book (34.13 MB)
1 Introduction to Logistic Regression With an Example (158.96 MB)
10 F-1 Score (29.56 MB)
11 ROCAUC (70.5 MB)
12 Summarizing Model Performance Metrices (52.11 MB)
13 Cross Validation (100.19 MB)
14 Model Selection (110.58 MB)
2 Explaining Sigmoid Function The Math Behind the Magic (171.58 MB)
3 Explaining Math of LogitLogistic Function (63.07 MB)
4 Logistic Regression Model Building (128.28 MB)
5 Model Evaluation (57.69 MB)
6 Model Evaluation Part 2 (7.34 MB)
7 Explaining Math of Model Accuracy Calculation (119.91 MB)
8 Confusion Matrix Math and Code (129.02 MB)
9 PrecisionRecall Calculation (101.65 MB)
1 Introduction to Multinomial Logistic Regression (78.28 MB)
2 Exercise (5.7 MB)
3 Solution Model Building (136.68 MB)
4 Accuracy Calculation (85.37 MB)
5 Confusion Matrix (74.08 MB)
6 PrecisionRecall (95.07 MB)
7 ROC and AUC (7.94 MB)
1 Introduction to Naive Bayes classifier (11.24 MB)
2 Model Building (80.63 MB)
3 Naive Bayes vs Logistic Regression (49.6 MB)
4 Multinomial Naive Bayes classifier (46.5 MB)
5 Text Classifier A Practical Example (128.03 MB)
1 Decision Tree Based Algorithm (36.24 MB)
2 Random Forest (50.52 MB)
3 Tree Visualization for Random Forest (161.55 MB)
4 Comparison of Classifiers (66.8 MB)
1 K-NN Classifier (43.78 MB)
2 Excercise (2.51 MB)
1 Bias (128.43 MB)
2 Variance (23.71 MB)
1 Data Science Career Prospects and Path (18.76 MB)
2 Data Science Job Search (5.81 MB)
3 Thank you! (8.74 MB)
1 Python Crash Course Overview (8.61 MB)
10 Example of Boolean Data Types (17.78 MB)
11 Conditional Statement in Python if else (36.4 MB)
12 Loop in Python (52.47 MB)
13 How to Write Function in Python (27.67 MB)
2 Simple Input and Output in Python (52.07 MB)
3 String in Python (101.8 MB)
4 Playing with Numbers (52.02 MB)
5 List in Python (173.26 MB)
6 Tuple (62.42 MB)
7 Dictionary in Python (95.71 MB)
8 More on Python Dictionary (32.68 MB)
9 Boolean in Python (74.84 MB)
1 Overview of data obtaining, cleaning and exploratory analysis (14.7 MB)
2 Reading Data From CSV File Part 1 (35.36 MB)
3 Reading Data From CSV File Part 2 (143.72 MB)
4 Reading Data From Excel File (31.17 MB)
5 Obtaining Data From SQL Server (139.86 MB)
6 Obtaining Data From API (97.31 MB)
1 Sanity Check (151.09 MB)
2 Data Cleaning (189.77 MB)
3 Data Cleaning Excercise (101.78 MB)
4 Solution to Data Cleaning Exercise, Part 1 (278.46 MB)
5 Pandas Apply Function (48.88 MB)
6 Solution to Data Cleaning Exercise, Part 2 (235.16 MB)
1 Exploratory Data Analysis Part 1 (290.12 MB)
2 Exploratory Data Analysis Part 2 (24.11 MB)
3 Exercise on EDA (43.45 MB)
4 Panda's Group By Function (49.88 MB)
5 Solution to EDA Exercise (258.59 MB)
1 Introduction to Data Visualization (25.52 MB)
10 Time Series Data Visualization Part 1 (144.36 MB)
11 Time Series Data Visualization Part 2 - Seaborn Example (61.98 MB)
12 Time Series Data Visualization Part 3 - Plotly Example (84.85 MB)
13 Plotly Installation Guideline (10.97 MB)
2 Line Plots (180.57 MB)
3 Different Types of Chart (74.35 MB)
4 Categorical Data Visualization Part 1 - Distribution Plots (123.55 MB)
5 Categorical Data Visualization Part 2 - Violin Plots (67.99 MB)
6 Categorical Data Visualization Part 3 - Violin Plots (69.53 MB)
7 Categorical Data Visualization Part 4 - Bar Plots and more (58.71 MB)
8 Spatial Data Visualization Part 1 (120.77 MB)
9 Spatial Data Visualization Part 2 (13.43 MB)
1 Data Wrangling Introduction (25.56 MB)
10 Aggregation Exercise Solution (106.27 MB)
11 Reshaping Part 1- Pivot (157.8 MB)
12 Reshaping Part 2 (Stacking) (97.14 MB)
13 Reshaping Part 3 (Unstacking) (10.91 MB)
14 MergeJoinConcatenation (77.29 MB)
15 Reshaping Exercise (6.22 MB)
16 Reshaping Exercise Solution (63.52 MB)
2 SlicingFiltering Part 1 (167.97 MB)
3 SlicingFiltering Part 2 (37.09 MB)
4 SlicingFiltering Part 3 (33.23 MB)
5 SlicingFiltering Part 4 (46.5 MB)
6 SlicingFiltering Part 5 (77.63 MB)
7 SlicingFiltering Part 6 (202.11 MB)
8 Aggregation (107.87 MB)
9 Aggregation Excercise (25.81 MB)
1 Introduction to Machine Learning with an Example (123.2 MB)
2 Different Types of Machine Learning (77.54 MB)
1 Introduction to Linear Regression (32.97 MB)
2 Linear Regression Part 1 (158.02 MB)
3 Linear Regression Part 2 (89.56 MB)
4 Model Metrics (59.17 MB)
5 Excercise (21.51 MB)
6 Exploratory Data Analysis for the Excercise (105.2 MB)
7 Solution of Exercise Feature Engineering (153.9 MB)
8 Solution of Exercise Model Building (81.24 MB)
9 Solution of Exercise Model Enhancement (124.91 MB)