Download Udemy - Complete 2020 Data Science & Machine Learning Bootcamp [Course Drive] Torrent

Torrent Contents Size: 14.83 GB

Udemy - Complete 2020 Data Science & Machine Learning Bootcamp [Course Drive]

Complete 2020 Data Science & Machine Learning Bootcamp

1. Introduction to the Course

1. What is Machine Learning.mp4	MP4	45.29 MB
1. What is Machine Learning.vtt	VTT	5.79 KB
2. What is Data Science.mp4	MP4	42.86 MB
2. What is Data Science.vtt	VTT	4.86 KB
3. Download the Syllabus.html	HTML	1.03 KB
3.1 ML Data Science Syllabus.pdf.pdf	PDF	103.97 KB
4. Top Tips for Succeeding on this Course.html	HTML	2.09 KB
4.1 App Brewery Cornell Notes Template.html	HTML	141 B
5. Course Resources List.html	HTML	1.13 KB
Must Read.txt	TXT	540 B
Visit Coursedrive.org.url	URL	124 B

10. Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow

1. Solving a Business Problem with Image Classification.mp4	MP4	30.52 MB
1. Solving a Business Problem with Image Classification.vtt	VTT	4.39 KB
1.1 Course Resources.html	HTML	122 B
10. Use the Model to Make Predictions.mp4	MP4	218.26 MB
10. Use the Model to Make Predictions.vtt	VTT	28.87 KB
11. Model Evaluation and the Confusion Matrix.mp4	MP4	62.76 MB
11. Model Evaluation and the Confusion Matrix.vtt	VTT	9.41 KB
12. Model Evaluation and the Confusion Matrix.mp4	MP4	251.84 MB
12. Model Evaluation and the Confusion Matrix.vtt	VTT	35.15 KB
13. Download the Complete Notebook Here.html	HTML	242 B
13.1 10 Neural Nets - Keras CIFAR10 Classification.ipynb.zip.zip	ZIP	120.11 KB
2. Installing Tensorflow and Keras for Jupyter.mp4	MP4	42.1 MB
2. Installing Tensorflow and Keras for Jupyter.vtt	VTT	5.72 KB
3. Gathering the CIFAR 10 Dataset.mp4	MP4	31.36 MB
3. Gathering the CIFAR 10 Dataset.vtt	VTT	5.42 KB
4. Exploring the CIFAR Data.mp4	MP4	110.31 MB
4. Exploring the CIFAR Data.vtt	VTT	15.81 KB
5. Pre-processing Scaling Inputs and Creating a Validation Dataset.mp4	MP4	93.16 MB
5. Pre-processing Scaling Inputs and Creating a Validation Dataset.mp4.jpg	JPG	71.56 KB
5. Pre-processing Scaling Inputs and Creating a Validation Dataset.txt	TXT	271 B
5. Pre-processing Scaling Inputs and Creating a Validation Dataset.vtt	VTT	17.4 KB
6. Compiling a Keras Model and Understanding the Cross Entropy Loss Function.mp4	MP4	103.61 MB
6. Compiling a Keras Model and Understanding the Cross Entropy Loss Function.vtt	VTT	16.31 KB
7. Interacting with the Operating System and the Python Try-Catch Block.mp4	MP4	133.41 MB
7. Interacting with the Operating System and the Python Try-Catch Block.vtt	VTT	20.8 KB
8. Fit a Keras Model and Use Tensorboard to Visualise Learning and Spot Problems.mp4	MP4	100.43 MB
8. Fit a Keras Model and Use Tensorboard to Visualise Learning and Spot Problems.vtt	VTT	12.36 KB
9. Use Regularisation to Prevent Overfitting Early Stopping & Dropout Techniques.vtt	VTT	24.62 KB

11. Use Tensorflow to Classify Handwritten Digits

1. What's coming up.mp4	MP4	7.1 MB
1. What's coming up.vtt	VTT	2.21 KB
1.1 Course Resources.html	HTML	122 B
10. Understanding the Tensorflow Graph Nodes and Edges.mp4	MP4	115.74 MB
10. Understanding the Tensorflow Graph Nodes and Edges.vtt	VTT	18.56 KB
11. Name Scoping and Image Visualisation in Tensorboard.mp4	MP4	155.37 MB
11. Name Scoping and Image Visualisation in Tensorboard.vtt	VTT	22.98 KB
12. Different Model Architectures Experimenting with Dropout.mp4	MP4	213.68 MB
12. Different Model Architectures Experimenting with Dropout.vtt	VTT	26.32 KB
13. Prediction and Model Evaluation.mp4	MP4	110.71 MB
13. Prediction and Model Evaluation.vtt	VTT	16.52 KB
14. Download the Complete Notebook Here.html	HTML	242 B
14.1 11 Neural Networks - TF Handwriting Recognition.ipynb.zip.zip	ZIP	6.6 KB
2. Getting the Data and Loading it into Numpy Arrays.mp4	MP4	52.82 MB
2. Getting the Data and Loading it into Numpy Arrays.vtt	VTT	7.91 KB
2.1 MNIST.zip.zip	ZIP	14.77 MB
3. Data Exploration and Understanding the Structure of the Input Data.mp4	MP4	32.41 MB
3. Data Exploration and Understanding the Structure of the Input Data.vtt	VTT	5.74 KB
4. Data Preprocessing One-Hot Encoding and Creating the Validation Dataset.mp4	MP4	70.18 MB
4. Data Preprocessing One-Hot Encoding and Creating the Validation Dataset.vtt	VTT	11.12 KB
5. What is a Tensor.mp4	MP4	45.39 MB
5. What is a Tensor.vtt	VTT	7.94 KB
6. Creating Tensors and Setting up the Neural Network Architecture.mp4	MP4	150.86 MB
6. Creating Tensors and Setting up the Neural Network Architecture.vtt	VTT	25.37 KB
7. Defining the Cross Entropy Loss Function, the Optimizer and the Metrics.mp4	MP4	75.12 MB
7. Defining the Cross Entropy Loss Function, the Optimizer and the Metrics.vtt	VTT	12.42 KB
8. TensorFlow Sessions and Batching Data.mp4	MP4	100.33 MB
8. TensorFlow Sessions and Batching Data.vtt	VTT	17.85 KB
9. Tensorboard Summaries and the Filewriter.mp4	MP4	128.29 MB
9. Tensorboard Summaries and the Filewriter.vtt	VTT	20.33 KB

12. Next Steps

1. Where next.html	HTML	3.93 KB
2. What Modules Do You Want to See.html	HTML	431 B
3. Stay in Touch!.html	HTML	1.05 KB
ReadMe.txt	TXT	538 B
Visit Coursedrive.org.url	URL	124 B

2. Predict Movie Box Office Revenue with Linear Regression

1. Introduction to Linear Regression & Specifying the Problem.mp4	MP4	30.33 MB
1. Introduction to Linear Regression & Specifying the Problem.vtt	VTT	7.28 KB
1.1 Course Resources.html	HTML	122 B
2. Gather & Clean the Data.mp4	MP4	97.02 MB
2. Gather & Clean the Data.vtt	VTT	11.74 KB
2.1 cost_revenue_dirty.csv.csv	CSV	374.68 KB
2.2 The-Numbers Movie Budgets.html	HTML	102 B
3. Explore & Visualise the Data with Python.mp4	MP4	148.16 MB
3. Explore & Visualise the Data with Python.vtt	VTT	26.38 KB
3.1 cost_revenue_clean.csv.csv	CSV	90.82 KB
3.2 Try Jupyter in your Browser.html	HTML	85 B
4. The Intuition behind the Linear Regression Model.mp4	MP4	29.63 MB
4. The Intuition behind the Linear Regression Model.vtt	VTT	9.14 KB
4.1 01 Linear Regression (checkpoint).ipynb.zip.zip	ZIP	37.64 KB
5. Analyse and Evaluate the Results.mp4	MP4	105.17 MB
5. Analyse and Evaluate the Results.vtt	VTT	18.88 KB
6. Download the Complete Notebook Here.html	HTML	242 B
6.1 01 Linear Regression (complete).ipynb.zip.zip	ZIP	75.28 KB
7. Join the Student Community.html	HTML	730 B

3. Python Programming for Data Science and Machine Learning

1. Windows Users - Install Anaconda.mp4	MP4	49.6 MB
1. Windows Users - Install Anaconda.vtt	VTT	7.46 KB
1.1 Course Resources.html	HTML	122 B
10. [Python] - Module Imports.mp4	MP4	232.08 MB
10. [Python] - Module Imports.vtt	VTT	30.42 KB
11. [Python] - Functions - Part 1 Defining and Calling Functions.mp4	MP4	41.61 MB
11. [Python] - Functions - Part 1 Defining and Calling Functions.vtt	VTT	8.86 KB
12. Python Functions Coding Exercise - Part 1.html	HTML	149 B
13. [Python] - Functions - Part 2 Arguments & Parameters.mp4	MP4	128.2 MB
13. [Python] - Functions - Part 2 Arguments & Parameters.vtt	VTT	17.58 KB
14. Python Functions Coding Exercise - Part 2.html	HTML	149 B
15. [Python] - Functions - Part 3 Results & Return Values.mp4	MP4	82.64 MB
15. [Python] - Functions - Part 3 Results & Return Values.vtt	VTT	14.05 KB
16. Python Functions Coding Exercise - Part 3.html	HTML	149 B
17. [Python] - Objects - Understanding Attributes and Methods.mp4	MP4	156.77 MB
17. [Python] - Objects - Understanding Attributes and Methods.vtt	VTT	25.19 KB
18. How to Make Sense of Python Documentation for Data Visualisation.mp4	MP4	171.46 MB
18. How to Make Sense of Python Documentation for Data Visualisation.vtt	VTT	22.49 KB
19. Working with Python Objects to Analyse Data.mp4	MP4	169.98 MB
19. Working with Python Objects to Analyse Data.vtt	VTT	22.97 KB
2. Mac Users - Install Anaconda.mp4	MP4	52.41 MB
2. Mac Users - Install Anaconda.vtt	VTT	6.83 KB
2.1 Course Resources.html	HTML	122 B
20. [Python] - Tips, Code Style and Naming Conventions.mp4	MP4	81.54 MB
20. [Python] - Tips, Code Style and Naming Conventions.vtt	VTT	14.12 KB
21. Download the Complete Notebook Here.html	HTML	242 B
21.1 02 Python Intro.ipynb.zip.zip	ZIP	36.44 KB
3. Does LSD Make You Better at Maths.mp4	MP4	42.26 MB
3. Does LSD Make You Better at Maths.vtt	VTT	6.23 KB
4. Download the 12 Rules to Learn to Code.html	HTML	1.13 KB
4.1 12 Rules to Learn to Code.pdf.pdf	PDF	2.25 MB
5. [Python] - Variables and Types.mp4	MP4	71.37 MB
5. [Python] - Variables and Types.vtt	VTT	14.2 KB
6. Python Variable Coding Exercise.html	HTML	149 B
7. [Python] - Lists and Arrays.mp4	MP4	53.47 MB
7. [Python] - Lists and Arrays.mp4.jpg	JPG	59 KB
7. [Python] - Lists and Arrays.txt	TXT	235 B
7. [Python] - Lists and Arrays.vtt	VTT	10.49 KB
8. Python Lists Coding Exercise.html	HTML	149 B
9. [Python & Pandas] - Dataframes and Series.mp4	MP4	153.21 MB
9. [Python & Pandas] - Dataframes and Series.vtt	VTT	24.01 KB
9.1 lsd_math_score_data.csv.csv	CSV	155 B

4. Introduction to Optimisation and the Gradient Descent Algorithm

1. What's Coming Up.mp4	MP4	20.93 MB
1. What's Coming Up.vtt	VTT	3.24 KB
1.1 Course Resources.html	HTML	122 B
10. Understanding the Learning Rate.mp4	MP4	236.6 MB
10. Understanding the Learning Rate.vtt	VTT	31.31 KB
11. How to Create 3-Dimensional Charts.mp4	MP4	193.48 MB
11. How to Create 3-Dimensional Charts.vtt	VTT	22.83 KB
12. Understanding Partial Derivatives and How to use SymPy.mp4	MP4	132.82 MB
12. Understanding Partial Derivatives and How to use SymPy.vtt	VTT	17.38 KB
13. Implementing Batch Gradient Descent with SymPy.mp4	MP4	86.83 MB
13. Implementing Batch Gradient Descent with SymPy.vtt	VTT	11.23 KB
14. [Python] - Loops and Performance Considerations.mp4	MP4	131.08 MB
14. [Python] - Loops and Performance Considerations.vtt	VTT	15.52 KB
15. Reshaping and Slicing N-Dimensional Arrays.mp4	MP4	140.82 MB
15. Reshaping and Slicing N-Dimensional Arrays.vtt	VTT	19.39 KB
16. Concatenating Numpy Arrays.mp4	MP4	71.33 MB
16. Concatenating Numpy Arrays.vtt	VTT	7.64 KB
17. Introduction to the Mean Squared Error (MSE).mp4	MP4	64.57 MB
17. Introduction to the Mean Squared Error (MSE).vtt	VTT	10.83 KB
18. Transposing and Reshaping Arrays.mp4	MP4	86.91 MB
18. Transposing and Reshaping Arrays.vtt	VTT	11.81 KB
19. Implementing a MSE Cost Function.mp4	MP4	81.12 MB
19. Implementing a MSE Cost Function.vtt	VTT	11.65 KB
2. How a Machine Learns.mp4	MP4	22.78 MB
2. How a Machine Learns.vtt	VTT	6.08 KB
20. Understanding Nested Loops and Plotting the MSE Function (Part 1).mp4	MP4	73.16 MB
20. Understanding Nested Loops and Plotting the MSE Function (Part 1).vtt	VTT	11.95 KB
21. Plotting the Mean Squared Error (MSE) on a Surface (Part 2).mp4	MP4	124.88 MB
21. Plotting the Mean Squared Error (MSE) on a Surface (Part 2).vtt	VTT	15.3 KB
22. Running Gradient Descent with a MSE Cost Function.mp4	MP4	111.22 MB
22. Running Gradient Descent with a MSE Cost Function.vtt	VTT	19.61 KB
23. Visualising the Optimisation on a 3D Surface.mp4	MP4	74.82 MB
23. Visualising the Optimisation on a 3D Surface.vtt	VTT	9.18 KB
24. Download the Complete Notebook Here.html	HTML	242 B
24.1 03 Gradient Descent.ipynb.zip.zip	ZIP	1.14 MB
3. Introduction to Cost Functions.mp4	MP4	66.2 MB
3. Introduction to Cost Functions.vtt	VTT	7.89 KB
4. LaTeX Markdown and Generating Data with Numpy.mp4	MP4	90.52 MB
4. LaTeX Markdown and Generating Data with Numpy.vtt	VTT	14.71 KB
5. Understanding the Power Rule & Creating Charts with Subplots.mp4	MP4	90.17 MB
5. Understanding the Power Rule & Creating Charts with Subplots.vtt	VTT	15.24 KB
6. [Python] - Loops and the Gradient Descent Algorithm.mp4	MP4	287.45 MB
6. [Python] - Loops and the Gradient Descent Algorithm.vtt	VTT	35.86 KB
7. Python Loops Coding Exercise.html	HTML	149 B
8. [Python] - Advanced Functions and the Pitfalls of Optimisation (Part 1).mp4	MP4	291.34 MB
8. [Python] - Advanced Functions and the Pitfalls of Optimisation (Part 1).vtt	VTT	36.4 KB
9. [Python] - Tuples and the Pitfalls of Optimisation (Part 2).mp4	MP4	219.02 MB
9. [Python] - Tuples and the Pitfalls of Optimisation (Part 2).vtt	VTT	28.47 KB

5. Predict House Prices with Multivariable Linear Regression

1. Defining the Problem.mp4	MP4	39.92 MB
1. Defining the Problem.vtt	VTT	5.45 KB
1.1 Course Resources.html	HTML	122 B
10. Calculating Correlations and the Problem posed by Multicollinearity.mp4	MP4	111.44 MB
10. Calculating Correlations and the Problem posed by Multicollinearity.vtt	VTT	15.25 KB
11. Visualising Correlations with a Heatmap.mp4	MP4	168.65 MB
11. Visualising Correlations with a Heatmap.vtt	VTT	20.68 KB
12. Techniques to Style Scatter Plots.mp4	MP4	128.53 MB
12. Techniques to Style Scatter Plots.vtt	VTT	17.68 KB
13. A Note for the Next Lesson.html	HTML	476 B
14. Working with Seaborn Pairplots & Jupyter Microbenchmarking Techniques.mp4	MP4	214.4 MB
14. Working with Seaborn Pairplots & Jupyter Microbenchmarking Techniques.vtt	VTT	24.44 KB
15. Understanding Multivariable Regression.mp4	MP4	48.81 MB
15. Understanding Multivariable Regression.vtt	VTT	6.38 KB
16. How to Shuffle and Split Training & Testing Data.mp4	MP4	64.35 MB
16. How to Shuffle and Split Training & Testing Data.vtt	VTT	10.08 KB
17. Running a Multivariable Regression.mp4	MP4	55.57 MB
17. Running a Multivariable Regression.vtt	VTT	8.44 KB
18. How to Calculate the Model Fit with R-Squared.mp4	MP4	32.4 MB
18. How to Calculate the Model Fit with R-Squared.vtt	VTT	3.85 KB
19. Introduction to Model Evaluation.mp4	MP4	15.99 MB
19. Introduction to Model Evaluation.vtt	VTT	3.2 KB
2. Gathering the Boston House Price Data.mp4	MP4	56.24 MB
2. Gathering the Boston House Price Data.vtt	VTT	7.35 KB
20. Improving the Model by Transforming the Data.mp4	MP4	126.87 MB
20. Improving the Model by Transforming the Data.vtt	VTT	18.69 KB
21. How to Interpret Coefficients using p-Values and Statistical Significance.mp4	MP4	65.4 MB
21. How to Interpret Coefficients using p-Values and Statistical Significance.vtt	VTT	9.46 KB
22. Understanding VIF & Testing for Multicollinearity.mp4	MP4	143.83 MB
22. Understanding VIF & Testing for Multicollinearity.vtt	VTT	22.11 KB
23. Model Simiplication & Baysian Information Criterion.mp4	MP4	150.15 MB
23. Model Simiplication & Baysian Information Criterion.vtt	VTT	19.9 KB
24. How to Analyse and Plot Regression Residuals.mp4	MP4	64.18 MB
24. How to Analyse and Plot Regression Residuals.vtt	VTT	12.41 KB
25. Residual Analysis (Part 1) Predicted vs Actual Values.mp4	MP4	124.42 MB
25. Residual Analysis (Part 1) Predicted vs Actual Values.vtt	VTT	15.41 KB
26. Residual Analysis (Part 2) Graphing and Comparing Regression Residuals.mp4	MP4	153.02 MB
26. Residual Analysis (Part 2) Graphing and Comparing Regression Residuals.vtt	VTT	19 KB
27. Making Predictions (Part 1) MSE & R-Squared.mp4	MP4	152.68 MB
27. Making Predictions (Part 1) MSE & R-Squared.vtt	VTT	20.07 KB
28. Making Predictions (Part 2) Standard Deviation, RMSE, and Prediction Intervals.mp4	MP4	84.85 MB
28. Making Predictions (Part 2) Standard Deviation, RMSE, and Prediction Intervals.vtt	VTT	12.66 KB
29. Build a Valuation Tool (Part 1) Working with Pandas Series & Numpy ndarrays.mp4	MP4	131.31 MB
29. Build a Valuation Tool (Part 1) Working with Pandas Series & Numpy ndarrays.vtt	VTT	17.95 KB
3. Clean and Explore the Data (Part 1) Understand the Nature of the Dataset.mp4	MP4	87.14 MB
3. Clean and Explore the Data (Part 1) Understand the Nature of the Dataset.vtt	VTT	13.29 KB
30. [Python] - Conditional Statements - Build a Valuation Tool (Part 2).mp4	MP4	134.39 MB
30. [Python] - Conditional Statements - Build a Valuation Tool (Part 2).vtt	VTT	18.5 KB
31. Python Conditional Statement Coding Exercise.html	HTML	149 B
32. Build a Valuation Tool (Part 3) Docstrings & Creating your own Python Module.mp4	MP4	244.16 MB
32. Build a Valuation Tool (Part 3) Docstrings & Creating your own Python Module.vtt	VTT	24.49 KB
33. Download the Complete Notebook Here.html	HTML	242 B
33.1 04 Multivariable Regression.ipynb.zip.zip	ZIP	3.55 MB
33.2 04 Valuation Tool.ipynb.zip.zip	ZIP	2.93 KB
4. Clean and Explore the Data (Part 2) Find Missing Values.mp4	MP4	135.03 MB
4. Clean and Explore the Data (Part 2) Find Missing Values.vtt	VTT	15.83 KB
5. Visualising Data (Part 1) Historams, Distributions & Outliers.mp4	MP4	64.56 MB
5. Visualising Data (Part 1) Historams, Distributions & Outliers.vtt	VTT	12.06 KB
6. Visualising Data (Part 2) Seaborn and Probability Density Functions.mp4	MP4	57.32 MB
6. Visualising Data (Part 2) Seaborn and Probability Density Functions.vtt	VTT	7.67 KB
7. Working with Index Data, Pandas Series, and Dummy Variables.mp4	MP4	140.77 MB
7. Working with Index Data, Pandas Series, and Dummy Variables.vtt	VTT	17.62 KB
8. Understanding Descriptive Statistics the Mean vs the Median.mp4	MP4	62.19 MB
8. Understanding Descriptive Statistics the Mean vs the Median.vtt	VTT	10.45 KB
9. Introduction to Correlation Understanding Strength & Direction.mp4	MP4	33.09 MB
9. Introduction to Correlation Understanding Strength & Direction.vtt	VTT	7.13 KB

6. Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1

1. How to Translate a Business Problem into a Machine Learning Problem.mp4	MP4	42.26 MB
1. How to Translate a Business Problem into a Machine Learning Problem.vtt	VTT	8.16 KB
1.1 Course Resources.html	HTML	122 B
10. Extracting the Text in the Email Body.mp4	MP4	47.43 MB
10. Extracting the Text in the Email Body.vtt	VTT	5.14 KB
11. [Python] - Generator Functions & the yield Keyword.mp4	MP4	133.16 MB
11. [Python] - Generator Functions & the yield Keyword.vtt	VTT	19.35 KB
12. Create a Pandas DataFrame of Email Bodies.mp4	MP4	48.67 MB
12. Create a Pandas DataFrame of Email Bodies.vtt	VTT	6.24 KB
13. Cleaning Data (Part 1) Check for Empty Emails & Null Entries.mp4	MP4	121.93 MB
13. Cleaning Data (Part 1) Check for Empty Emails & Null Entries.vtt	VTT	15.32 KB
14. Cleaning Data (Part 2) Working with a DataFrame Index.mp4	MP4	61.83 MB
14. Cleaning Data (Part 2) Working with a DataFrame Index.vtt	VTT	8.12 KB
15. Saving a JSON File with Pandas.mp4	MP4	56.35 MB
15. Saving a JSON File with Pandas.vtt	VTT	6.02 KB
16. Data Visualisation (Part 1) Pie Charts.mp4	MP4	90.69 MB
16. Data Visualisation (Part 1) Pie Charts.vtt	VTT	13.9 KB
17. Data Visualisation (Part 2) Donut Charts.mp4	MP4	61.79 MB
17. Data Visualisation (Part 2) Donut Charts.vtt	VTT	8.11 KB
18. Introduction to Natural Language Processing (NLP).mp4	MP4	50.81 MB
18. Introduction to Natural Language Processing (NLP).vtt	VTT	7 KB
19. Tokenizing, Removing Stop Words and the Python Set Data Structure.mp4	MP4	117.76 MB
19. Tokenizing, Removing Stop Words and the Python Set Data Structure.vtt	VTT	15.99 KB
2. Gathering Email Data and Working with Archives & Text Editors.mp4	MP4	112.05 MB
2. Gathering Email Data and Working with Archives & Text Editors.vtt	VTT	11.89 KB
2.1 SpamData.zip.zip	ZIP	21.28 MB
20. Word Stemming & Removing Punctuation.mp4	MP4	71.44 MB
20. Word Stemming & Removing Punctuation.vtt	VTT	8.98 KB
21. Removing HTML tags with BeautifulSoup.mp4	MP4	95.82 MB
21. Removing HTML tags with BeautifulSoup.vtt	VTT	9.51 KB
22. Creating a Function for Text Processing.mp4	MP4	53.91 MB
23. A Note for the Next Lesson.html	HTML	476 B
24. Advanced Subsetting on DataFrames the apply() Function.mp4	MP4	83.4 MB
24. Advanced Subsetting on DataFrames the apply() Function.vtt	VTT	11.62 KB
25. [Python] - Logical Operators to Create Subsets and Indices.mp4	MP4	86.41 MB
26. Word Clouds & How to install Additional Python Packages.mp4	MP4	79.49 MB
26. Word Clouds & How to install Additional Python Packages.vtt	VTT	10.14 KB
27. Creating your First Word Cloud.mp4	MP4	98.44 MB
27. Creating your First Word Cloud.vtt	VTT	11.87 KB
28. Styling the Word Cloud with a Mask.mp4	MP4	131.37 MB
28. Styling the Word Cloud with a Mask.vtt	VTT	14.23 KB
29. Solving the Hamlet Challenge.mp4	MP4	57.11 MB
29. Solving the Hamlet Challenge.vtt	VTT	5.26 KB
3. How to Add the Lesson Resources to the Project.mp4	MP4	28.91 MB
3. How to Add the Lesson Resources to the Project.vtt	VTT	4.08 KB
30. Styling Word Clouds with Custom Fonts.mp4	MP4	127.3 MB
30. Styling Word Clouds with Custom Fonts.vtt	VTT	12.55 KB
31. Create the Vocabulary for the Spam Classifier.mp4	MP4	106.97 MB
31. Create the Vocabulary for the Spam Classifier.vtt	VTT	15.37 KB
32. Coding Challenge Check for Membership in a Collection.mp4	MP4	32.35 MB
32. Coding Challenge Check for Membership in a Collection.vtt	VTT	5.08 KB
33. Coding Challenge Find the Longest Email.mp4	MP4	54.47 MB
33. Coding Challenge Find the Longest Email.vtt	VTT	6.51 KB
34. Sparse Matrix (Part 1) Split the Training and Testing Data.mp4	MP4	87.63 MB
34. Sparse Matrix (Part 1) Split the Training and Testing Data.vtt	VTT	13.43 KB
35. Sparse Matrix (Part 2) Data Munging with Nested Loops.mp4	MP4	137.23 MB
35. Sparse Matrix (Part 2) Data Munging with Nested Loops.vtt	VTT	19.8 KB
36. Sparse Matrix (Part 3) Using groupby() and Saving .txt Files.mp4	MP4	80.5 MB
36. Sparse Matrix (Part 3) Using groupby() and Saving .txt Files.vtt	VTT	10.63 KB
37. Coding Challenge Solution Preparing the Test Data.mp4	MP4	28.93 MB
37. Coding Challenge Solution Preparing the Test Data.vtt	VTT	4.25 KB
38. Checkpoint Understanding the Data.mp4	MP4	96.37 MB
38. Checkpoint Understanding the Data.vtt	VTT	12 KB
39. Download the Complete Notebook Here.html	HTML	242 B
39.1 06 Bayes Classifier - Pre-Processing.ipynb.zip.zip	ZIP	988.02 KB
4. The Naive Bayes Algorithm and the Decision Boundary for a Classifier.mp4	MP4	33.39 MB
4. The Naive Bayes Algorithm and the Decision Boundary for a Classifier.vtt	VTT	5.18 KB
5. Basic Probability.mp4	MP4	28.56 MB
5. Basic Probability.vtt	VTT	4.54 KB
6. Joint & Conditional Probability.mp4	MP4	141.82 MB
6. Joint & Conditional Probability.vtt	VTT	16.75 KB
7. Bayes Theorem.mp4	MP4	83.12 MB
7. Bayes Theorem.vtt	VTT	12.8 KB
8. Reading Files (Part 1) Absolute Paths and Relative Paths.mp4	MP4	60.9 MB
8. Reading Files (Part 1) Absolute Paths and Relative Paths.vtt	VTT	10.01 KB
9. Reading Files (Part 2) Stream Objects and Email Structure.mp4	MP4	104.33 MB
9. Reading Files (Part 2) Stream Objects and Email Structure.vtt	VTT	12.37 KB

7. Train a Naive Bayes Classifier to Create a Spam Filter Part 2

1. Setting up the Notebook and Understanding Delimiters in a Dataset.mp4	MP4	72.5 MB
1. Setting up the Notebook and Understanding Delimiters in a Dataset.vtt	VTT	9.79 KB
1.1 SpamData.zip.zip	ZIP	22.32 MB
1.2 Course Resources.html	HTML	122 B
2. Create a Full Matrix.mp4	MP4	132.24 MB
2. Create a Full Matrix.vtt	VTT	18.82 KB
3. Count the Tokens to Train the Naive Bayes Model.mp4	MP4	96.19 MB
3. Count the Tokens to Train the Naive Bayes Model.vtt	VTT	16.02 KB
4. Sum the Tokens across the Spam and Ham Subsets.mp4	MP4	46.71 MB
4. Sum the Tokens across the Spam and Ham Subsets.vtt	VTT	6.89 KB
5. Calculate the Token Probabilities and Save the Trained Model.mp4	MP4	53.46 MB
5. Calculate the Token Probabilities and Save the Trained Model.vtt	VTT	8.24 KB
6. Coding Challenge Prepare the Test Data.mp4	MP4	35.6 MB
6. Coding Challenge Prepare the Test Data.vtt	VTT	4.52 KB
7. Download the Complete Notebook Here.html	HTML	242 B
7.1 07 Bayes Classifier - Training.ipynb.zip.zip	ZIP	5.82 KB

8. Test and Evaluate a Naive Bayes Classifier Part 3

1. Set up the Testing Notebook.mp4	MP4	26.45 MB
1. Set up the Testing Notebook.vtt	VTT	3.32 KB
1.1 Course Resources.html	HTML	122 B
1.2 SpamData.zip.zip	ZIP	22.83 MB
10. The F-score or F1 Metric.mp4	MP4	24.72 MB
10. The F-score or F1 Metric.vtt	VTT	4.03 KB
11. A Naive Bayes Implementation using SciKit Learn.mp4	MP4	195.1 MB
11. A Naive Bayes Implementation using SciKit Learn.vtt	VTT	29.17 KB
12. Download the Complete Notebook Here.html	HTML	242 B
12.1 08 Naive Bayes with scikit-learn.ipynb.zip.zip	ZIP	13.26 KB
12.2 07 Bayes Classifier - Testing, Inference & Evaluation.ipynb.zip.zip	ZIP	243.05 KB
2. Joint Conditional Probability (Part 1) Dot Product.mp4	MP4	66.41 MB
2. Joint Conditional Probability (Part 1) Dot Product.vtt	VTT	11.15 KB
3. Joint Conditional Probablity (Part 2) Priors.mp4	MP4	63.98 MB
3. Joint Conditional Probablity (Part 2) Priors.vtt	VTT	9.34 KB
4. Making Predictions Comparing Joint Probabilities.mp4	MP4	52.34 MB
4. Making Predictions Comparing Joint Probabilities.vtt	VTT	8.53 KB
5. The Accuracy Metric.mp4	MP4	40.54 MB
5. The Accuracy Metric.vtt	VTT	6.69 KB
6. Visualising the Decision Boundary.mp4	MP4	205.31 MB
6. Visualising the Decision Boundary.vtt	VTT	29.22 KB
7. False Positive vs False Negatives.mp4	MP4	63.25 MB
7. False Positive vs False Negatives.vtt	VTT	11.22 KB
8. The Recall Metric.mp4	MP4	28.16 MB
8. The Recall Metric.vtt	VTT	5.74 KB
9. The Precision Metric.mp4	MP4	53.34 MB
9. The Precision Metric.vtt	VTT	8.32 KB

9. Introduction to Neural Networks and How to Use Pre-Trained Models

1. The Human Brain and the Inspiration for Artificial Neural Networks.mp4	MP4	51.81 MB
1. The Human Brain and the Inspiration for Artificial Neural Networks.vtt	VTT	9.6 KB
1.1 Course Resources.html	HTML	122 B
2. Layers, Feature Generation and Learning.mp4	MP4	146.7 MB
2. Layers, Feature Generation and Learning.vtt	VTT	24.25 KB
3. Costs and Disadvantages of Neural Networks.mp4	MP4	91.99 MB
3. Costs and Disadvantages of Neural Networks.vtt	VTT	16.81 KB
4. Preprocessing Image Data and How RGB Works.mp4	MP4	93.61 MB
4. Preprocessing Image Data and How RGB Works.vtt	VTT	14.12 KB
4.1 TF_Keras_Classification_Images.zip.zip	ZIP	501.1 KB
5. Importing Keras Models and the Tensorflow Graph.mp4	MP4	65.47 MB
5. Importing Keras Models and the Tensorflow Graph.vtt	VTT	10.11 KB
6. Making Predictions using InceptionResNet.mp4	MP4	134.58 MB
6. Making Predictions using InceptionResNet.vtt	VTT	16.48 KB
7. Coding Challenge Solution Using other Keras Models.mp4	MP4	103.54 MB
7. Coding Challenge Solution Using other Keras Models.vtt	VTT	11.41 KB
8. Download the Complete Notebook Here.html	HTML	264 B
8.1 09 Neural Nets Pretrained Image Classification.ipynb.zip.zip	ZIP	571.83 KB

ReadMe.txt

TXT

538 B

Visit Coursedrive.org.url

URL

124 B

Course Downloaded from coursedrive.org.txt

TXT

538 B

Visit Coursedrive.org.url

URL

124 B

Description

Show full description

Related Torrents

TORRENT NAME	SIZE	FILES	AGE	SEED	LEECH	SOURCE
Udemy - Unity for Game Testers - Complete masterclass for beginners Posted by freecoursewb in Other Posted in Other 1 4.3 GB 3 months ago freecoursewb	Size 4.3 GB	Files 261	Age 3 months ago	Seeds 1	Leechs 32	Source
Udemy - Master Viscous Flow in Pipes - A Complete Guide Posted by freecoursewb in Other Posted in Other 0 1 GB 3 months ago freecoursewb	Size 1 GB	Files 10	Age 3 months ago	Seeds 0	Leechs 0	Source
Udemy - Master Unit Testing in C# with xUnit - The Complete Guide Posted by freecoursewb in Other Posted in Other 0 2 GB 3 months ago freecoursewb	Size 2 GB	Files 22	Age 3 months ago	Seeds 0	Leechs 0	Source
Udemy - Major Gift Fundraising for Nonprofits - Complete Guide Posted by freecoursewb in Other Posted in Other 0 969.6 MB 3 months ago freecoursewb	Size 969.6 MB	Files 11	Age 3 months ago	Seeds 0	Leechs 0	Source
Udemy - Complete Lightweight Charts Bootcamp - From Basics to Advance Posted by freecoursewb in Other Posted in Other 0 2.8 GB 3 months ago freecoursewb	Size 2.8 GB	Files 173	Age 3 months ago	Seeds 0	Leechs 0	Source

Udemy - Complete 2020 Data Science & Machine Learning Bootcamp [Course Drive]

Torrent Contents Size: 14.83 GB

Description

Related Torrents

Location

Trackers

Latest News

Latest Searches

Sites In Our Index

Popular Tags

Tracker name
udp://tracker.coppersurfer.tk:6969/announce
udp://tracker.leechers-paradise.org:6969/announce
udp://tracker.opentrackr.org:1337/announce
udp://p4p.arenabg.com:1337/announce
udp://9.rarbg.to:2710/announce
udp://9.rarbg.me:2710/announce
udp://exodus.desync.com:6969/announce
udp://tracker.pomf.se:80/announce
udp://tracker.openbittorrent.com:80/announce
udp://tracker.tiny-vps.com:6969/announce
udp://open.stealth.si:80/announce
udp://tracker.torrent.eu.org:451/announce
udp://tracker.cyberia.is:6969/announce
udp://torrentclub.tech:6969/announce
udp://tracker.zer0day.to:1337/announce
udp://tracker.leechers-paradise.org:6969/announce
udp://coppersurfer.tk:6969/announce