2023 Python for Machine Learning & Data Science Projects

سرفصل های دوره

1. 1 Python Crash Course

1. Introduction.html

2. Arithmatic Operations in Python

3. Data Types in Python

4. Variable Casting

5. Strings Operation in Python

6. String Slicing in Python

7. String Formatting and Modification

8. Boolean Variables and Evaluation

9. List in Python

10. Tuple in Python

11. 10 Set

12. Dictionary

13. Conditional Statements - If Else

14. While Loops

15. For Loops

16. Functions

17. Working with Date and Time

18. File Handling Read and Write

2. Numpy Crash Course

1. Numpy Introduction - Create Numpy Array

2. Array Indexing and Slicing

3. Numpy Data Types

4. np.nan and np.inf

5. Statistical Operations

6. Shape(), Reshape(), Ravel(), Flatten()

7. arange(), linspace(), range(), random(), zeros(), and ones()

8. Where

9. Numpy Array Read and Write

10. Concatenation and Sorting

3. Pandas for Data Analysis

1. Pandas Series Introduction Part 1

2. Pandas Series Introduction Part 2

3. Pandas Series Read From File

4. Apply Pythons Built in Functions to Series

5. apply() for Pandas Series

6. Pandas DataFrame Creation from Scratch

7. Read Files as DataFrame

8. Columns Manipulation Part 1

9. Columns Manipulation Part 2

10. Arithmetic Operations

11. NULL Values Handling

12. DataFrame Data Filtering Part 1

13. DataFrame Data Filtering Part 2

14. 14 Handling Unique and Duplicated Values

15. Retrive Rows by Index Label

16. Replace Cell Values

17. Rename, Delete Index and Columns

18. Lambda Apply

19. Pandas Groupby

20. Groupby Multiple Columns

21. Merging, Joining, and Concatenation Part 1

22. Concatenation

23. Merge and Join

24. Working with Datetime

25. Read Stock Data from YAHOO Finance

4. Matplotlib for Data Analysis

1. Matplotlib Introduction

2. Matplotlib Line Plot Part 1

3. IMDB Movie Revenue Line Plot Part 1

4. IMDB Movie Revenue Line Plot Part 2

5. Line Plot Rank vs Runtime Votes Metascore

6. Line Styling and Putting Labels

7. Scatter, Bar, and Histogram Plot Part 1

8. Scatter, Bar, and Histogram Plot Part 2

9. Subplot Part 1

10. Subplot Part 2

11. Subplots

12. Creating a Zoomed Sub-Figure of a Figure

13. xlim and ylim, legend, grid, xticks, yticks

14. Pie Chart and Figure Save

5. Seaborn for Data Analysis

1. Introduction

2. Scatter Plot

3. Hue, Style and Size Part1

4. Hue, Style and Size Part2

5. Line Plot Part 1

6. Line Plot Part 2

7. Line Plot Part 3

8. Subplots

9. sns.lineplot() and sns.scatterplot()

10. cat plot

11. Box Plot

12. Boxen Plot

13. Violin Plot

14. Bar Plot

15. Point Plot

16. Joint Plot

17. Pair Plot

18. Regression Plot

19. Controlling Ploted Figure Aesthetics

6. Data Visualization in Pandas

1. IRIS Dataset Introduction

2. Load IRIS Dataset

3. Line Plot

4. Secondary Axis

5. Bar and Barh Plot

6. Stacked Bar Plot

7. Histogram

8. Box Plot

9. Area and Scatter Plot

10. Hexbin Plot

11. Pie Chart

12. Scatter Matrix and Subplots

7. Data Visualization Plotly

1. Introduction to Plotly and Cufflinks

2. Plotly Line Plot

3. Scatter Plot

4. Stacked Bar Plot

5. Box and Area Plot

6. 3D Plot

7. Hist Plot, Bubble Plot and Heatmap

8. Linear Regression

1. Linear Regression Introduction

2. Regression Examples

3. Types of Linear Regression

4. Assessing the performance of the model

5. Bias-Variance tradeoff

6. What is sklearn and train-test-split

7. Python Package Upgrade and Import

8. Load Boston Housing Dataset

9. Dataset Analysis

10. Exploratory Data Analysis- Pair Plot

11. Exploratory Data Analysis- Hist Plot

12. Exploratory Data Analysis- Heatmap

13. Train Test Split and Model Training

14. How to Evaluate the Regression Model Performance

15. Plot True House Price vs Predicted Price

16. Plotting Learning Curves Part 1

17. Plotting Learning Curves Part 2

18. Machine Learning Model Interpretability- Residuals Plot

19. Machine Learning Model Interpretability- Prediction Error Plot

53,700 تومان

خرید اشتراک افزودن به سبد خرید

خرید دانلودی فوری

در این روش نیاز به افزودن محصول به سبد خرید و تکمیل اطلاعات نیست و شما پس از وارد کردن ایمیل خود و طی کردن مراحل پرداخت لینک های دریافت محصولات را در ایمیل خود دریافت خواهید کرد.

تولید کننده: Udemy-Training