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| Item Details | Price | ||
|---|---|---|---|
Data Science
Instructor: Sahir
Validity Period: Lifetime
₹50000 28% OFF
₹35800 including 18% GST
No Description Available
| 1. Course Introduction | |||
| 1 3:00 | |||
| 2. Environment Set-Up | |||
| 1. Environment Set-Up 8:00 | |||
| 3. Jupyter Overview | |||
| 2. Jupyter Notebooks_x264 13:00 | |||
| 3. Optional Virtual Environments 9:00 | |||
| Python Crash Course | |||
| ._2. Introduction to Python Crash Course 1:00 | |||
| 3. Python Crash Course - Part 1 19:00 | |||
| 4. Python Crash Course - Part 2_x264 15:00 | |||
| 5. Python Crash Course - Part 3 16:00 | |||
| 6. Python Crash Course - Part 4 15:00 | |||
| 7. Python Crash Course Exercises - Overview_x264 3:00 | |||
| 8. Python Crash Course Exercises - Solutions 12:00 | |||
| 5. Python for Data Analysis - NumPy | |||
| ._2. Introduction to Numpy_x264 2:00 | |||
| 3. Numpy Arrays_x264 16:00 | |||
| 5. Numpy Array Indexing_x264 18:00 | |||
| 6. Numpy Operations_x264 7:00 | |||
| 7. Numpy Exercises Overview_x264 2:00 | |||
| 8. Numpy Exercises Solutions_x264 15:00 | |||
| 6. Python for Data Analysis - Pandas | |||
| 2. Introduction to Pandas_x264 1:00 | |||
| 3. Series_x264 10:00 | |||
| 4. DataFrames - Part 1_x264 15:00 | |||
| 5. DataFrames - Part 2_x264 17:00 | |||
| 6. DataFrames - Part 3_x264 9:00 | |||
| 7. Missing Data_x264 6:00 | |||
| 8. Groupby_x264 7:00 | |||
| 9. Merging Joining and Concatenating_x264 9:00 | |||
| 10. Operations_x264 13:00 | |||
| 11. Data Input and Output_x264 14:00 | |||
| 7. Python for Data Analysis - Pandas Exercises | |||
| 1. SF Salaries Exercise Overview_x264 1:00 | |||
| 3. SF Salaries Solutions_x264 15:00 | |||
| 4. Ecommerce Purchases Exercise Overview_x264 2:00 | |||
| 5. Ecommerce Purchases Exercise Solutions_x264 15:00 | |||
| 8. Python for Data Visualization - Matplotlib | |||
| 2. Introduction to Matplotlib_x264 3:00 | |||
| 3. Matplotlib Part 1_x264 17:00 | |||
| 4. Matplotlib Part 2_x264 15:00 | |||
| 5. Matplotlib Part 3_x264 11:00 | |||
| 6. Matplotlib Exercises Overview_x264 1:00 | |||
| 7. Matplotlib Exercises - Solutions_x264 10:00 | |||
| 9. Python for Data Visualization - Seaborn | |||
| 1. Introduction to Seaborn_x264 3:00 | |||
| 2. Distribution Plots_x264 18:00 | |||
| 3. Categorical Plots_x264 17:00 | |||
| 4. Matrix Plots_x264 10:00 | |||
| 5. Grids_x264 8:00 | |||
| 6. Regression Plots_x264 7:00 | |||
| 7. Style and Color_x264 8:00 | |||
| 8. Seaborn Exercise Overview_x264 2:00 | |||
| 9. Seaborn Exercise Solutions_x264 7:00 | |||
| 13. Data Capstone Project | |||
| 2. 911 Calls Project Overview_x264 1:00 | |||
| 3. 911 Calls Solutions - Part 1_x264 14:00 | |||
| 4. 911 Calls Solutions - Part 2_x264 19:00 | |||
| 6. Finance Data Project Overview_x264 3:00 | |||
| 7. Finance Project - Solutions Part 1_x264 17:00 | |||
| 8. Finance Project - Solutions Part 2_x264 18:00 | |||
| 9. Finance Project - Solutions Part 3_x264 6:00 | |||
| 14. Introduction to Machine Learning | |||
| 1. Welcome to the Machine Learning Section-FMT | |||
| 3. Introduction to Machine Learning_x264 10:00 | |||
| 4. Machine Learning with Python_x264 9:00 | |||
| 15. Linear Regression | |||
| 1. Linear Regression Theory_x264 4:00 | |||
| 3. Linear Regression with Python - Part 1_x264 18:00 | |||
| 4. Linear Regression with Python - Part 2_x264 7:00 | |||
| 5. Linear Regression Project Overview_x264 2:00 | |||
| 6. Linear Regression Project Solution_x264 18:00 | |||
| 16. Cross Validation and Bias-Variance Trade-Off | |||
| 1. Bias Variance Trade-Off_x264 6:00 | |||
| 17. Logistic Regression | |||
| 1.Logistic Regression Theory_264 10:00 | |||
| 2. Logistic Regression with Python - Part 1_x264 14:00 | |||
| 3. Logistic Regression with Python - Part 2_x264 16:00 | |||
| 4. Logistic Regression with Python - Part 3_x264 7:00 | |||
| 5. Logistic Regression Project Overview_x264 1:00 | |||
| 6. Logistic Regression Project Solutions_x264 11:00 | |||
| 18. K Nearest Neighbors | |||
| 1. KNN Theory_x264 5:00 | |||
| 2. KNN with Python_x264 19:00 | |||
| 3. KNN Project Overview_x264 1:00 | |||
| 4. KNN Project Solutions_x264 14:00 | |||
| 19. Decision Trees and Random Forests | |||
| 1. Introduction to Tree Methods_x264 6:00 | |||
| 2. Decision Trees and Random Forest with Python_x264 14:00 | |||
| 3. Decision Trees and Random Forest Project Overview_x264 3:00 | |||
| 4. Decision Trees and Random Forest Solutions Part 1_x264 12:00 | |||
| 5. Decision Trees and Random Forest Solutions Part 2_x264 9:00 | |||
| 20. Support Vector Machines | |||
| 1. SVM Theory_x264 4:00 | |||
| 2. Support Vector Machines with Python_x264 18:00 | |||
| 3. SVM Project Overview_x264 2:00 | |||
| 4. SVM Project Solutions_x264 10:00 | |||
| 21. K Means Clustering | |||
| 1. K Means Algorithm Theory_x264 5:00 | |||
| 2. K Means with Python_x264 12:00 | |||
| 3. K Means Project Overview_x264 3:00 | |||
| 4. K Means Project Solutions_x264 17:00 | |||
| 22. Principal Component Analysis | |||
| 1. Principal Component Analysis_x264 3:00 | |||
| 2. PCA with Python_x264 16:00 | |||
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