Download TensorFlow Developer Certificate in 2021: Zero to Mastery Torrent

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TensorFlow Developer Certificate in 2021: Zero to Mastery

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1. Introduction

1. Course Outline.mp4	MP4	58.03 MB
1. Course Outline.srt	SRT	7.97 KB
2. Join Our Online Classroom!.html	HTML	2.43 KB
3. Exercise Meet The Community.html	HTML	2.83 KB
4. All Course Resources + Notebooks.html	HTML	1.97 KB
4.1 Zero to Mastery TensorFlow Deep Learning on GitHub.html	HTML	114 B

10. NLP Fundamentals in TensorFlow

	1. More Videos Coming Soon!.html	HTML	41 B
	GetFreeCourses.Co.url	URL	116 B

11. Milestone Project 2 SkimLit

1. More Videos Coming Soon!.html

HTML

41 B

12. Time Series fundamentals in TensorFlow

1. More Videos Coming Soon!.html

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41 B

13. Milestone Project 3 BitPredict

1. More Videos Coming Soon!.html

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41 B

14. Passing the TensorFlow Developer Certificate Exam

1. More Videos Coming Soon!.html

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41 B

15. Where To Go From Here

1. Become An Alumni.html	HTML	944 B
2. LinkedIn Endorsements.html	HTML	2.05 KB
3. TensorFlow Certificate.html	HTML	385 B
4. Course Review.html	HTML	176 B
5. The Final Challenge.html	HTML	176 B

16. Appendix Machine Learning Primer

1. Quick Note Upcoming Videos.html	HTML	706 B
10. Section Review.mp4	MP4	5.56 MB
10. Section Review.srt	SRT	2.2 KB
2. What is Machine Learning.mp4	MP4	28.31 MB
2. What is Machine Learning.srt	SRT	8.95 KB
3. AIMachine LearningData Science.mp4	MP4	19.67 MB
3. AIMachine LearningData Science.srt	SRT	6.45 KB
4. Exercise Machine Learning Playground.mp4	MP4	42.56 MB
4. Exercise Machine Learning Playground.srt	SRT	8.13 KB
4.1 httpsteachablemachine.withgoogle.com.html	HTML	101 B
5. How Did We Get Here.mp4	MP4	30.49 MB
5. How Did We Get Here.srt	SRT	7.34 KB
6. Exercise YouTube Recommendation Engine.mp4	MP4	19.43 MB
6. Exercise YouTube Recommendation Engine.srt	SRT	5.61 KB
6.1 httpsml-playground.com#.html	HTML	88 B
7. Types of Machine Learning.mp4	MP4	22.81 MB
7. Types of Machine Learning.srt	SRT	5.51 KB
8. Are You Getting It Yet.html	HTML	160 B
9. What Is Machine Learning Round 2.mp4	MP4	25.51 MB
9. What Is Machine Learning Round 2.srt	SRT	6.25 KB

17. Appendix Machine Learning and Data Science Framework

1. Quick Note Upcoming Videos.html	HTML	706 B
10. Modelling - Picking the Model.mp4	MP4	23.24 MB
10. Modelling - Picking the Model.srt	SRT	6.23 KB
11. Modelling - Tuning.mp4	MP4	15.98 MB
11. Modelling - Tuning.srt	SRT	5.09 KB
12. Modelling - Comparison.mp4	MP4	44.86 MB
12. Modelling - Comparison.srt	SRT	13.32 KB
13. Overfitting and Underfitting Definitions.html	HTML	1.97 KB
14. Experimentation.mp4	MP4	21.3 MB
14. Experimentation.srt	SRT	5.09 KB
15. Tools We Will Use.mp4	MP4	27.34 MB
15. Tools We Will Use.srt	SRT	6.08 KB
16. Optional Elements of AI.html	HTML	975 B
2. Section Overview.mp4	MP4	13.34 MB
2. Section Overview.srt	SRT	4.79 KB
3. Introducing Our Framework.mp4	MP4	11.39 MB
3. Introducing Our Framework.srt	SRT	3.7 KB
4. 6 Step Machine Learning Framework.mp4	MP4	23.45 MB
4. 6 Step Machine Learning Framework.srt	SRT	6.86 KB
4.1 6 Step Guide.html	HTML	147 B
5. Types of Machine Learning Problems.mp4	MP4	60.46 MB
5. Types of Machine Learning Problems.srt	SRT	14.46 KB
6. Types of Data.mp4	MP4	29.31 MB
6. Types of Data.srt	SRT	6.48 KB
7. Types of Evaluation.mp4	MP4	17.74 MB
7. Types of Evaluation.srt	SRT	4.56 KB
8. Features In Data.mp4	MP4	36.78 MB
8. Features In Data.srt	SRT	6.88 KB
9. Modelling - Splitting Data.mp4	MP4	27.55 MB
9. Modelling - Splitting Data.srt	SRT	7.79 KB

18. Appendix Pandas for Data Analysis

1. Quick Note Upcoming Videos.html	HTML	706 B
10. Manipulating Data.mp4	MP4	105 MB
10. Manipulating Data.srt	SRT	18.56 KB
10.1 car-sales-missing-data.csv	CSV	287 B
10.2 httpsjakevdp.github.ioPythonDataScienceHandbook03.00-introduction-to-pandas.html.html	HTML	146 B
11. Manipulating Data 2.mp4	MP4	86.56 MB
11. Manipulating Data 2.srt	SRT	14.82 KB
11.1 pandas-anatomy-of-a-dataframe.png	PNG	333.24 KB
12. Manipulating Data 3.mp4	MP4	91.07 MB
12. Manipulating Data 3.srt	SRT	14 KB
12.1 Pandas video notes.html	HTML	185 B
12.2 Pandas video code.html	HTML	191 B
13. Assignment Pandas Practice.html	HTML	2.05 KB
14. How To Download The Course Assignments.mp4	MP4	66.79 MB
14. How To Download The Course Assignments.srt	SRT	11.24 KB
14.1 Course Notes.html	HTML	108 B
14.2 httpscolab.research.google.com.html	HTML	95 B
2. Section Overview.mp4	MP4	10.87 MB
2. Section Overview.srt	SRT	3.69 KB
3. Downloading Workbooks and Assignments.html	HTML	967 B
4. Pandas Introduction.mp4	MP4	27.46 MB
4. Pandas Introduction.srt	SRT	6.91 KB
4.1 10 Minutes to pandas.html	HTML	127 B
4.2 Intro to pandas code.html	HTML	191 B
4.3 Intro to pandas notes.html	HTML	185 B
5. Series, Data Frames and CSVs.mp4	MP4	95.43 MB
5. Series, Data Frames and CSVs.srt	SRT	18.45 KB
5.1 pandas-anatomy-of-a-dataframe.png	PNG	333.24 KB
6. Data from URLs.html	HTML	1.09 KB
7. Describing Data with Pandas.mp4	MP4	75.65 MB
7. Describing Data with Pandas.srt	SRT	14.22 KB
8. Selecting and Viewing Data with Pandas.mp4	MP4	72.29 MB
8. Selecting and Viewing Data with Pandas.srt	SRT	15.22 KB
8.1 car-sales.csv	CSV	369 B
9. Selecting and Viewing Data with Pandas Part 2.mp4	MP4	106.49 MB
9. Selecting and Viewing Data with Pandas Part 2.srt	SRT	18.95 KB

19. Appendix NumPy

1. Quick Note Upcoming Videos.html	HTML	706 B
10. Manipulating Arrays 2.mp4	MP4	67.91 MB
10. Manipulating Arrays 2.srt	SRT	12.01 KB
10.1 httpswww.mathsisfun.comdatastandard-deviation.html.html	HTML	116 B
11. Standard Deviation and Variance.mp4	MP4	51.13 MB
11. Standard Deviation and Variance.srt	SRT	9.81 KB
11.1 httpswww.mathsisfun.comdatastandard-deviation.html.html	HTML	116 B
12. Reshape and Transpose.mp4	MP4	53.57 MB
12. Reshape and Transpose.srt	SRT	9.68 KB
13. Dot Product vs Element Wise.mp4	MP4	83.8 MB
13. Dot Product vs Element Wise.srt	SRT	15.89 KB
13.1 httpswww.mathsisfun.comalgebramatrix-multiplying.html.html	HTML	119 B
14. Exercise Nut Butter Store Sales.mp4	MP4	91.27 MB
14. Exercise Nut Butter Store Sales.srt	SRT	17.41 KB
15. Comparison Operators.mp4	MP4	26.38 MB
15. Comparison Operators.srt	SRT	5.22 KB
16. Sorting Arrays.mp4	MP4	32.82 MB
16. Sorting Arrays.srt	SRT	8.95 KB
17. Turn Images Into NumPy Arrays.mp4	MP4	85.98 MB
17. Turn Images Into NumPy Arrays.srt	SRT	10.6 KB
17.1 numpy-images.zip	ZIP	7.27 MB
17.2 NumPy Video code.html	HTML	190 B
17.3 Section Notes.html	HTML	184 B
18. Assignment NumPy Practice.html	HTML	2.17 KB
19. Optional Extra NumPy resources.html	HTML	1.02 KB
2. Section Overview.mp4	MP4	13.36 MB
2. Section Overview.srt	SRT	3.24 KB
3. NumPy Introduction.mp4	MP4	26.86 MB
3. NumPy Introduction.srt	SRT	7.6 KB
3.1 httpsnumpy.orgdoc.html	HTML	83 B
3.2 NumPy Video code.html	HTML	190 B
3.3 NumPy Notes.html	HTML	184 B
4. Quick Note Correction In Next Video.html	HTML	1.25 KB
5. NumPy DataTypes and Attributes.mp4	MP4	78.97 MB
5. NumPy DataTypes and Attributes.srt	SRT	20.04 KB
6. Creating NumPy Arrays.mp4	MP4	66.84 MB
6. Creating NumPy Arrays.srt	SRT	12.45 KB
7. NumPy Random Seed.mp4	MP4	51.95 MB
7. NumPy Random Seed.srt	SRT	10.44 KB
8. Viewing Arrays and Matrices.mp4	MP4	70.66 MB
8. Viewing Arrays and Matrices.srt	SRT	13.86 KB
9. Manipulating Arrays.mp4	MP4	80.67 MB
9. Manipulating Arrays.srt	SRT	17.14 KB
9.1 httpswww.mathsisfun.comdatastandard-deviation.html.html	HTML	116 B

2. Deep Learning and TensorFlow Fundamentals

1. What is deep learning.mp4	MP4	34.17 MB
1. What is deep learning.srt	SRT	6.8 KB
1.1 All course materials and links!.html	HTML	114 B
10. Creating your first tensors with TensorFlow and tf.constant().mp4	MP4	134.83 MB
10. Creating your first tensors with TensorFlow and tf.constant().srt	SRT	24.75 KB
11. Creating tensors with TensorFlow and tf.Variable().mp4	MP4	70.85 MB
11. Creating tensors with TensorFlow and tf.Variable().srt	SRT	9.9 KB
12. Creating random tensors with TensorFlow.mp4	MP4	88.45 MB
12. Creating random tensors with TensorFlow.srt	SRT	13.03 KB
13. Shuffling the order of tensors.mp4	MP4	89.86 MB
13. Shuffling the order of tensors.srt	SRT	12.63 KB
14. Creating tensors from NumPy arrays.mp4	MP4	101.34 MB
14. Creating tensors from NumPy arrays.srt	SRT	15.03 KB
15. Getting information from your tensors (tensor attributes).mp4	MP4	87.39 MB
15. Getting information from your tensors (tensor attributes).srt	SRT	16.96 KB
16. Indexing and expanding tensors.mp4	MP4	86.57 MB
16. Indexing and expanding tensors.srt	SRT	16.96 KB
17. Manipulating tensors with basic operations.mp4	MP4	45.22 MB
17. Manipulating tensors with basic operations.srt	SRT	6.95 KB
18. Matrix multiplication with tensors part 1.mp4	MP4	100.85 MB
18. Matrix multiplication with tensors part 1.srt	SRT	15.22 KB
19. Matrix multiplication with tensors part 2.mp4	MP4	107.79 MB
19. Matrix multiplication with tensors part 2.srt	SRT	17.35 KB
2. Why use deep learning.mp4	MP4	62.32 MB
2. Why use deep learning.srt	SRT	14.19 KB
20. Matrix multiplication with tensors part 3.mp4	MP4	80.62 MB
20. Matrix multiplication with tensors part 3.srt	SRT	13.27 KB
21. Changing the datatype of tensors.mp4	MP4	71.39 MB
21. Changing the datatype of tensors.srt	SRT	8.64 KB
22. Tensor aggregation (finding the min, max, mean & more).mp4	MP4	89.58 MB
22. Tensor aggregation (finding the min, max, mean & more).srt	SRT	12.88 KB
23. Tensor troubleshooting example (updating tensor datatypes).mp4	MP4	69.39 MB
23. Tensor troubleshooting example (updating tensor datatypes).srt	SRT	6.63 KB
24. Finding the positional minimum and maximum of a tensor (argmin and argmax).mp4	MP4	96.5 MB
24. Finding the positional minimum and maximum of a tensor (argmin and argmax).srt	SRT	12.38 KB
25. Squeezing a tensor (removing all 1-dimension axes).mp4	MP4	30.2 MB
25. Squeezing a tensor (removing all 1-dimension axes).srt	SRT	3.84 KB
26. One-hot encoding tensors.mp4	MP4	59.73 MB
26. One-hot encoding tensors.srt	SRT	7.98 KB
27. Trying out more tensor math operations.mp4	MP4	55.93 MB
27. Trying out more tensor math operations.srt	SRT	6.23 KB
28. Exploring TensorFlow and NumPy's compatibility.mp4	MP4	43.75 MB
28. Exploring TensorFlow and NumPy's compatibility.srt	SRT	7.11 KB
29. Making sure our tensor operations run really fast on GPUs.mp4	MP4	110.91 MB
29. Making sure our tensor operations run really fast on GPUs.srt	SRT	14.45 KB
3. What are neural networks.mp4	MP4	63.43 MB
3. What are neural networks.srt	SRT	14.7 KB
30. TensorFlow Fundamentals challenge, exercises & extra-curriculum.html	HTML	1.95 KB
31. Python + Machine Learning Monthly.html	HTML	796 B
32. LinkedIn Endorsements.html	HTML	2.05 KB
4. What is deep learning already being used for.mp4	MP4	76.21 MB
4. What is deep learning already being used for.srt	SRT	13.48 KB
5. What is and why use TensorFlow.mp4	MP4	69.16 MB
5. What is and why use TensorFlow.srt	SRT	11.74 KB
6. What is a Tensor.mp4	MP4	27.58 MB
6. What is a Tensor.srt	SRT	4.99 KB
7. What we're going to cover throughout the course.mp4	MP4	29.38 MB
7. What we're going to cover throughout the course.srt	SRT	7.23 KB
8. How to approach this course.mp4	MP4	26.18 MB
8. How to approach this course.srt	SRT	8.24 KB
9. Need A Refresher.html	HTML	942 B

20. BONUS SECTION

1. Special Bonus Lecture.html

HTML

3.65 KB

3. Neural network regression with TensorFlow

1. Introduction to Neural Network Regression with TensorFlow.mp4	MP4	60.06 MB
1. Introduction to Neural Network Regression with TensorFlow.srt	SRT	11.41 KB
1.1 All course materials and links (notebooks, code, data, slides) on GitHub.html	HTML	114 B
10. Evaluating a TensorFlow model part 2 (the three datasets).mp4	MP4	81.56 MB
10. Evaluating a TensorFlow model part 2 (the three datasets).srt	SRT	14.05 KB
11. Evaluating a TensorFlow model part 3 (getting a model summary).mp4	MP4	192.79 MB
11. Evaluating a TensorFlow model part 3 (getting a model summary).srt	SRT	21.53 KB
12. Evaluating a TensorFlow model part 4 (visualising a model's layers).mp4	MP4	70.28 MB
12. Evaluating a TensorFlow model part 4 (visualising a model's layers).srt	SRT	9.23 KB
13. Evaluating a TensorFlow model part 5 (visualising a model's predictions).mp4	MP4	78.88 MB
13. Evaluating a TensorFlow model part 5 (visualising a model's predictions).srt	SRT	11.92 KB
14. Evaluating a TensorFlow model part 6 (common regression evaluation metrics).mp4	MP4	70.37 MB
14. Evaluating a TensorFlow model part 6 (common regression evaluation metrics).srt	SRT	11.16 KB
15. Evaluating a TensorFlow regression model part 7 (mean absolute error).mp4	MP4	56.09 MB
15. Evaluating a TensorFlow regression model part 7 (mean absolute error).srt	SRT	8.1 KB
16. Evaluating a TensorFlow regression model part 7 (mean square error).mp4	MP4	32.31 MB
16. Evaluating a TensorFlow regression model part 7 (mean square error).srt	SRT	3.88 KB
17. Setting up TensorFlow modelling experiments part 1 (start with a simple model).mp4	MP4	127.26 MB
17. Setting up TensorFlow modelling experiments part 1 (start with a simple model).srt	SRT	17.44 KB
18. Setting up TensorFlow modelling experiments part 2 (increasing complexity).mp4	MP4	95.63 MB
18. Setting up TensorFlow modelling experiments part 2 (increasing complexity).srt	SRT	15.86 KB
19. Comparing and tracking your TensorFlow modelling experiments.mp4	MP4	92.25 MB
19. Comparing and tracking your TensorFlow modelling experiments.srt	SRT	13.18 KB
2. Inputs and outputs of a neural network regression model.mp4	MP4	57.57 MB
2. Inputs and outputs of a neural network regression model.srt	SRT	13.12 KB
20. How to save a TensorFlow model.mp4	MP4	92.29 MB
20. How to save a TensorFlow model.srt	SRT	11.39 KB
21. How to load and use a saved TensorFlow model.mp4	MP4	104.37 MB
21. How to load and use a saved TensorFlow model.srt	SRT	12.81 KB
22. (Optional) How to save and download files from Google Colab.mp4	MP4	67.7 MB
22. (Optional) How to save and download files from Google Colab.srt	SRT	7.79 KB
23. Putting together what we've learned part 1 (preparing a dataset).mp4	MP4	143.51 MB
23. Putting together what we've learned part 1 (preparing a dataset).srt	SRT	18.7 KB
24. Putting together what we've learned part 2 (building a regression model).mp4	MP4	121.38 MB
24. Putting together what we've learned part 2 (building a regression model).srt	SRT	17.95 KB
25. Putting together what we've learned part 3 (improving our regression model).mp4	MP4	155.11 MB
25. Putting together what we've learned part 3 (improving our regression model).srt	SRT	18.8 KB
26. Preprocessing data with feature scaling part 1 (what is feature scaling).mp4	MP4	92.51 MB
26. Preprocessing data with feature scaling part 1 (what is feature scaling).srt	SRT	13.88 KB
27. Preprocessing data with feature scaling part 2 (normalising our data).mp4	MP4	97.18 MB
27. Preprocessing data with feature scaling part 2 (normalising our data).srt	SRT	13.93 KB
28. Preprocessing data with feature scaling part 3 (fitting a model on scaled data).mp4	MP4	75.72 MB
28. Preprocessing data with feature scaling part 3 (fitting a model on scaled data).srt	SRT	10.97 KB
29. TensorFlow Regression challenge, exercises & extra-curriculum.html	HTML	1.98 KB
3. Anatomy and architecture of a neural network regression model.mp4	MP4	59 MB
3. Anatomy and architecture of a neural network regression model.srt	SRT	12.25 KB
4. Creating sample regression data (so we can model it).mp4	MP4	90.16 MB
4. Creating sample regression data (so we can model it).srt	SRT	16.12 KB
5. The major steps in modelling with TensorFlow.mp4	MP4	181.81 MB
5. The major steps in modelling with TensorFlow.srt	SRT	25.74 KB
6. Steps in improving a model with TensorFlow part 1.mp4	MP4	45.82 MB
6. Steps in improving a model with TensorFlow part 1.srt	SRT	7.62 KB
7. Steps in improving a model with TensorFlow part 2.mp4	MP4	90.23 MB
7. Steps in improving a model with TensorFlow part 2.srt	SRT	13.12 KB
8. Steps in improving a model with TensorFlow part 3.mp4	MP4	132.94 MB
8. Steps in improving a model with TensorFlow part 3.srt	SRT	16.84 KB
9. Evaluating a TensorFlow model part 1 (visualise, visualise, visualise).mp4	MP4	66.94 MB
9. Evaluating a TensorFlow model part 1 (visualise, visualise, visualise).srt	SRT	9.77 KB

4. Neural network classification in TensorFlow

1. Introduction to neural network classification in TensorFlow.mp4	MP4	72.81 MB
1. Introduction to neural network classification in TensorFlow.srt	SRT	12.76 KB
1.1 All course materials and links (notebooks, code, data, slides) on GitHub.html	HTML	119 B
10. Make our poor classification model work for a regression dataset.mp4	MP4	123.01 MB
10. Make our poor classification model work for a regression dataset.srt	SRT	16.33 KB
11. Non-linearity part 1 Straight lines and non-straight lines.mp4	MP4	95.62 MB
11. Non-linearity part 1 Straight lines and non-straight lines.srt	SRT	13.79 KB
12. Non-linearity part 2 Building our first neural network with non-linearity.mp4	MP4	59 MB
12. Non-linearity part 2 Building our first neural network with non-linearity.srt	SRT	7.58 KB
13. Non-linearity part 3 Upgrading our non-linear model with more layers.mp4	MP4	123.24 MB
13. Non-linearity part 3 Upgrading our non-linear model with more layers.srt	SRT	14.34 KB
14. Non-linearity part 4 Modelling our non-linear data once and for all.mp4	MP4	96.62 MB
14. Non-linearity part 4 Modelling our non-linear data once and for all.srt	SRT	11.99 KB
15. Non-linearity part 5 Replicating non-linear activation functions from scratch.mp4	MP4	146.61 MB
15. Non-linearity part 5 Replicating non-linear activation functions from scratch.srt	SRT	18.28 KB
16. Getting great results in less time by tweaking the learning rate.mp4	MP4	136.78 MB
16. Getting great results in less time by tweaking the learning rate.srt	SRT	19.38 KB
17. Using the TensorFlow History object to plot a model's loss curves.mp4	MP4	62.12 MB
17. Using the TensorFlow History object to plot a model's loss curves.srt	SRT	8.38 KB
18. Using callbacks to find a model's ideal learning rate.mp4	MP4	155.88 MB
18. Using callbacks to find a model's ideal learning rate.srt	SRT	24.87 KB
19. Training and evaluating a model with an ideal learning rate.mp4	MP4	89.01 MB
19. Training and evaluating a model with an ideal learning rate.srt	SRT	11.87 KB
2. Example classification problems (and their inputs and outputs).mp4	MP4	50.71 MB
2. Example classification problems (and their inputs and outputs).srt	SRT	9.89 KB
20. Introducing more classification evaluation methods.mp4	MP4	42.21 MB
20. Introducing more classification evaluation methods.srt	SRT	8.87 KB
21. Finding the accuracy of our classification model.mp4	MP4	34.07 MB
21. Finding the accuracy of our classification model.srt	SRT	5.63 KB
22. Creating our first confusion matrix (to see where our model is getting confused).mp4	MP4	65.7 MB
22. Creating our first confusion matrix (to see where our model is getting confused).srt	SRT	11.54 KB
23. Making our confusion matrix prettier.mp4	MP4	114.12 MB
23. Making our confusion matrix prettier.srt	SRT	18.28 KB
24. Putting things together with multi-class classification part 1 Getting the data.mp4	MP4	87.22 MB
24. Putting things together with multi-class classification part 1 Getting the data.srt	SRT	13.77 KB
25. Multi-class classification part 2 Becoming one with the data.mp4	MP4	48.65 MB
25. Multi-class classification part 2 Becoming one with the data.srt	SRT	9.99 KB
26. Multi-class classification part 3 Building a multi-class classification model.mp4	MP4	142.8 MB
26. Multi-class classification part 3 Building a multi-class classification model.srt	SRT	21.13 KB
27. Multi-class classification part 4 Improving performance with normalisation.mp4	MP4	113.41 MB
27. Multi-class classification part 4 Improving performance with normalisation.srt	SRT	16.21 KB
28. Multi-class classification part 5 Comparing normalised and non-normalised data.mp4	MP4	26.77 MB
28. Multi-class classification part 5 Comparing normalised and non-normalised data.srt	SRT	5.44 KB
29. Multi-class classification part 6 Finding the ideal learning rate.mp4	MP4	73.34 MB
29. Multi-class classification part 6 Finding the ideal learning rate.srt	SRT	14.91 KB
3. Input and output tensors of classification problems.mp4	MP4	51.01 MB
3. Input and output tensors of classification problems.srt	SRT	8.85 KB
30. Multi-class classification part 7 Evaluating our model.mp4	MP4	119.14 MB
30. Multi-class classification part 7 Evaluating our model.srt	SRT	16.96 KB
31. Multi-class classification part 8 Creating a confusion matrix.mp4	MP4	40.52 MB
31. Multi-class classification part 8 Creating a confusion matrix.srt	SRT	6.67 KB
32. Multi-class classification part 9 Visualising random model predictions.mp4	MP4	65.68 MB
32. Multi-class classification part 9 Visualising random model predictions.srt	SRT	13.52 KB
33. What patterns is our model learning.mp4	MP4	127.96 MB
33. What patterns is our model learning.srt	SRT	20.83 KB
34. TensorFlow classification challenge, exercises & extra-curriculum.html	HTML	2.48 KB
4. Typical architecture of neural network classification models with TensorFlow.mp4	MP4	112.73 MB
4. Typical architecture of neural network classification models with TensorFlow.srt	SRT	14.61 KB
5. Creating and viewing classification data to model.mp4	MP4	106.08 MB
5. Creating and viewing classification data to model.srt	SRT	14.39 KB
6. Checking the input and output shapes of our classification data.mp4	MP4	38.15 MB
6. Checking the input and output shapes of our classification data.srt	SRT	6.57 KB
7. Building a not very good classification model with TensorFlow.mp4	MP4	125.29 MB
7. Building a not very good classification model with TensorFlow.srt	SRT	16.03 KB
8. Trying to improve our not very good classification model.mp4	MP4	84.29 MB
8. Trying to improve our not very good classification model.srt	SRT	12.67 KB
9. Creating a function to view our model's not so good predictions.mp4	MP4	160.55 MB
9. Creating a function to view our model's not so good predictions.srt	SRT	18.99 KB

5. Computer Vision and Convolutional Neural Networks in TensorFlow

1. Introduction to Computer Vision with TensorFlow.mp4	MP4	75.01 MB
1. Introduction to Computer Vision with TensorFlow.srt	SRT	15 KB
10. Improving our non-CNN model by adding more layers.mp4	MP4	106.47 MB
10. Improving our non-CNN model by adding more layers.srt	SRT	13.98 KB
11. Breaking our CNN model down part 1 Becoming one with the data.mp4	MP4	90.92 MB
11. Breaking our CNN model down part 1 Becoming one with the data.srt	SRT	13 KB
12. Breaking our CNN model down part 2 Preparing to load our data.mp4	MP4	109.48 MB
12. Breaking our CNN model down part 2 Preparing to load our data.srt	SRT	16.51 KB
14. Breaking our CNN model down part 4 Building a baseline CNN model.mp4	MP4	85.3 MB
14. Breaking our CNN model down part 4 Building a baseline CNN model.srt	SRT	11.22 KB
15. Breaking our CNN model down part 5 Looking inside a Conv2D layer.mp4	MP4	186.04 MB
15. Breaking our CNN model down part 5 Looking inside a Conv2D layer.srt	SRT	22.79 KB
15.1 CNN Explainer website.html	HTML	102 B
2. Introduction to Convolutional Neural Networks (CNNs) with TensorFlow.mp4	MP4	76.65 MB
2. Introduction to Convolutional Neural Networks (CNNs) with TensorFlow.srt	SRT	12.11 KB
20. Breaking our CNN model down part 10 Visualizing our augmented data.mp4	MP4	157.62 MB
20. Breaking our CNN model down part 10 Visualizing our augmented data.srt	SRT	21.55 KB
24. Downloading a custom image to make predictions on.mp4	MP4	53.08 MB
24. Downloading a custom image to make predictions on.srt	SRT	6.93 KB
25. Writing a helper function to load and preprocessing custom images.mp4	MP4	105.15 MB
25. Writing a helper function to load and preprocessing custom images.srt	SRT	13.73 KB
26. Making a prediction on a custom image with our trained CNN.mp4	MP4	99.9 MB
26. Making a prediction on a custom image with our trained CNN.srt	SRT	15.46 KB
27. Multi-class CNN's part 1 Becoming one with the data.mp4	MP4	140.19 MB
27. Multi-class CNN's part 1 Becoming one with the data.srt	SRT	22.69 KB
28. Multi-class CNN's part 2 Preparing our data (turning it into tensors).mp4	MP4	72.72 MB
28. Multi-class CNN's part 2 Preparing our data (turning it into tensors).srt	SRT	9.95 KB
29. Multi-class CNN's part 3 Building a multi-class CNN model.mp4	MP4	89.24 MB
29. Multi-class CNN's part 3 Building a multi-class CNN model.srt	SRT	10.65 KB
3. Downloading an image dataset for our first Food Vision model.mp4	MP4	72.94 MB
3. Downloading an image dataset for our first Food Vision model.srt	SRT	10.31 KB
30. Multi-class CNN's part 4 Fitting a multi-class CNN model to the data.mp4	MP4	59.66 MB
30. Multi-class CNN's part 4 Fitting a multi-class CNN model to the data.srt	SRT	8.96 KB
31. Multi-class CNN's part 5 Evaluating our multi-class CNN model.mp4	MP4	41.05 MB
31. Multi-class CNN's part 5 Evaluating our multi-class CNN model.srt	SRT	6.79 KB
32. Multi-class CNN's part 6 Trying to fix overfitting by removing layers.mp4	MP4	129.83 MB
32. Multi-class CNN's part 6 Trying to fix overfitting by removing layers.srt	SRT	16.43 KB
34. Multi-class CNN's part 8 Things you could do to improve your CNN model.mp4	MP4	43.29 MB
34. Multi-class CNN's part 8 Things you could do to improve your CNN model.srt	SRT	6.18 KB
36. Saving and loading our trained CNN model.mp4	MP4	69.28 MB
36. Saving and loading our trained CNN model.srt	SRT	9.07 KB
4. Becoming One With Data.mp4	MP4	45.61 MB
4. Becoming One With Data.srt	SRT	6.72 KB
5. Becoming One With Data Part 2.mp4	MP4	104.59 MB
5. Becoming One With Data Part 2.srt	SRT	16.06 KB
6. Becoming One With Data Part 3.mp4	MP4	39.89 MB
6. Becoming One With Data Part 3.srt	SRT	6.54 KB
7. Building an end to end CNN Model.mp4	MP4	155.09 MB
7. Building an end to end CNN Model.srt	SRT	26 KB
8. Using a GPU to run our CNN model 5x faster.mp4	MP4	114.94 MB
8. Using a GPU to run our CNN model 5x faster.srt	SRT	13.05 KB
9. Trying a non-CNN model on our image data.mp4	MP4	100.56 MB
9. Trying a non-CNN model on our image data.srt	SRT	11.63 KB

6. Transfer Learning in TensorFlow Part 1 Feature extraction

1. What is and why use transfer learning.mp4	MP4	65.81 MB
1. What is and why use transfer learning.srt	SRT	15.94 KB
1.1 All course materials and links (notebooks, code, data, slides) on GitHub.html	HTML	114 B
10. Comparing Our Model's Results.mp4	MP4	143.93 MB
10. Comparing Our Model's Results.srt	SRT	21.56 KB
11. TensorFlow Transfer Learning Part 1 challenge, exercises & extra-curriculum.html	HTML	2.44 KB
2. Downloading and preparing data for our first transfer learning model.mp4	MP4	132.67 MB
2. Downloading and preparing data for our first transfer learning model.srt	SRT	18.11 KB
3. Introducing Callbacks in TensorFlow and making a callback to track our models.mp4	MP4	94.89 MB
3. Introducing Callbacks in TensorFlow and making a callback to track our models.srt	SRT	14.26 KB
4. Exploring the TensorFlow Hub website for pretrained models.mp4	MP4	102.96 MB
4. Exploring the TensorFlow Hub website for pretrained models.srt	SRT	14.67 KB
5. Building and compiling a TensorFlow Hub feature extraction model.mp4	MP4	135.63 MB
5. Building and compiling a TensorFlow Hub feature extraction model.srt	SRT	18.91 KB
6. Blowing our previous models out of the water with transfer learning.mp4	MP4	99.46 MB
6. Blowing our previous models out of the water with transfer learning.srt	SRT	13.66 KB
7. Plotting the loss curves of our ResNet feature extraction model.mp4	MP4	62.09 MB
7. Plotting the loss curves of our ResNet feature extraction model.srt	SRT	10.81 KB
8. Building and training a pre-trained EfficientNet model on our data.mp4	MP4	105.93 MB
8. Building and training a pre-trained EfficientNet model on our data.srt	SRT	14.27 KB
9. Different Types of Transfer Learning.mp4	MP4	110.57 MB
9. Different Types of Transfer Learning.srt	SRT	15.67 KB
GetFreeCourses.Co.url	URL	116 B

7. Transfer Learning in TensorFlow Part 2 Fine tuning

1. Introduction to Transfer Learning in TensorFlow Part 2 Fine-tuning.mp4	MP4	61.46 MB
1. Introduction to Transfer Learning in TensorFlow Part 2 Fine-tuning.srt	SRT	9.78 KB
10. Downloading and preparing the data for Model 1 (1 percent of training data).mp4	MP4	97.8 MB
10. Downloading and preparing the data for Model 1 (1 percent of training data).srt	SRT	12.98 KB
11. Building a data augmentation layer to use inside our model.mp4	MP4	117.46 MB
11. Building a data augmentation layer to use inside our model.srt	SRT	16.15 KB
12. Visualising what happens when images pass through our data augmentation layer.mp4	MP4	119.36 MB
12. Visualising what happens when images pass through our data augmentation layer.srt	SRT	14.4 KB
13. Building Model 1 (with a data augmentation layer and 1% of training data).mp4	MP4	152.95 MB
13. Building Model 1 (with a data augmentation layer and 1% of training data).srt	SRT	22.42 KB
14. Building Model 2 (with a data augmentation layer and 10% of training data).mp4	MP4	159.77 MB
14. Building Model 2 (with a data augmentation layer and 10% of training data).srt	SRT	23.45 KB
15. Creating a ModelCheckpoint to save our model's weights during training.mp4	MP4	68.99 MB
15. Creating a ModelCheckpoint to save our model's weights during training.srt	SRT	10.72 KB
16. Fitting and evaluating Model 2 (and saving its weights using ModelCheckpoint).mp4	MP4	68.15 MB
16. Fitting and evaluating Model 2 (and saving its weights using ModelCheckpoint).srt	SRT	9.85 KB
17. Loading and comparing saved weights to our existing trained Model 2.mp4	MP4	62.67 MB
17. Loading and comparing saved weights to our existing trained Model 2.srt	SRT	9.65 KB
18. Preparing Model 3 (our first fine-tuned model).mp4	MP4	198.23 MB
18. Preparing Model 3 (our first fine-tuned model).srt	SRT	25.9 KB
19. Fitting and evaluating Model 3 (our first fine-tuned model).mp4	MP4	69.16 MB
19. Fitting and evaluating Model 3 (our first fine-tuned model).srt	SRT	10.61 KB
2. Importing a script full of helper functions (and saving lots of space).mp4	MP4	89.39 MB
2. Importing a script full of helper functions (and saving lots of space).srt	SRT	9.77 KB
20. Comparing our model's results before and after fine-tuning.mp4	MP4	84.18 MB
20. Comparing our model's results before and after fine-tuning.srt	SRT	13.82 KB
21. Downloading and preparing data for our biggest experiment yet (Model 4).mp4	MP4	56.68 MB
21. Downloading and preparing data for our biggest experiment yet (Model 4).srt	SRT	8.97 KB
22. Preparing our final modelling experiment (Model 4).mp4	MP4	96.42 MB
22. Preparing our final modelling experiment (Model 4).srt	SRT	14.88 KB
23. Fine-tuning Model 4 on 100% of the training data and evaluating its results.mp4	MP4	96.84 MB
23. Fine-tuning Model 4 on 100% of the training data and evaluating its results.srt	SRT	14.85 KB
24. Comparing our modelling experiment results in TensorBoard.mp4	MP4	95.75 MB
24. Comparing our modelling experiment results in TensorBoard.srt	SRT	15.74 KB
25. How to view and delete previous TensorBoard experiments.mp4	MP4	21.91 MB
25. How to view and delete previous TensorBoard experiments.srt	SRT	2.81 KB
26. Transfer Learning in TensorFlow Part 2 challenge, exercises and extra-curriculum.html	HTML	2.64 KB
3. Downloading and turning our images into a TensorFlow BatchDataset.mp4	MP4	173.6 MB
3. Downloading and turning our images into a TensorFlow BatchDataset.srt	SRT	22.01 KB
4. Discussing the four (actually five) modelling experiments we're running.mp4	MP4	15.87 MB
4. Discussing the four (actually five) modelling experiments we're running.srt	SRT	3.58 KB
5. Comparing the TensorFlow Keras Sequential API versus the Functional API.mp4	MP4	26.45 MB
5. Comparing the TensorFlow Keras Sequential API versus the Functional API.srt	SRT	4.03 KB
6. Creating our first model with the TensorFlow Keras Functional API.mp4	MP4	132.18 MB
6. Creating our first model with the TensorFlow Keras Functional API.srt	SRT	15.84 KB
7. Compiling and fitting our first Functional API model.mp4	MP4	132.84 MB
7. Compiling and fitting our first Functional API model.srt	SRT	15.76 KB
8. Getting a feature vector from our trained model.mp4	MP4	147.62 MB
8. Getting a feature vector from our trained model.srt	SRT	17.74 KB
9. Drilling into the concept of a feature vector (a learned representation).mp4	MP4	51.5 MB
9. Drilling into the concept of a feature vector (a learned representation).srt	SRT	5.39 KB

8. Transfer Learning with TensorFlow Part 3 Scaling Up

1. Introduction to Transfer Learning Part 3 Scaling Up.mp4	MP4	41.53 MB
1. Introduction to Transfer Learning Part 3 Scaling Up.srt	SRT	10.12 KB
10. Downloading a pretrained model to make and evaluate predictions with.mp4	MP4	78.69 MB
10. Downloading a pretrained model to make and evaluate predictions with.srt	SRT	8.91 KB
11. Making predictions with our trained model on 25,250 test samples.mp4	MP4	115.59 MB
11. Making predictions with our trained model on 25,250 test samples.srt	SRT	16.24 KB
12. Unravelling our test dataset for comparing ground truth labels to predictions.mp4	MP4	43.81 MB
12. Unravelling our test dataset for comparing ground truth labels to predictions.srt	SRT	7.72 KB
13. Confirming our model's predictions are in the same order as the test labels.mp4	MP4	50.54 MB
13. Confirming our model's predictions are in the same order as the test labels.srt	SRT	6.77 KB
14. Creating a confusion matrix for our model's 101 different classes.mp4	MP4	156.6 MB
14. Creating a confusion matrix for our model's 101 different classes.srt	SRT	17.49 KB
15. Evaluating every individual class in our dataset.mp4	MP4	131.77 MB
15. Evaluating every individual class in our dataset.srt	SRT	19.3 KB
16. Plotting our model's F1-scores for each separate class.mp4	MP4	77.94 MB
16. Plotting our model's F1-scores for each separate class.srt	SRT	10.69 KB
17. Creating a function to load and prepare images for making predictions.mp4	MP4	109.54 MB
17. Creating a function to load and prepare images for making predictions.srt	SRT	15.79 KB
18. Making predictions on our test images and evaluating them.mp4	MP4	171.68 MB
18. Making predictions on our test images and evaluating them.srt	SRT	23.48 KB
19. Discussing the benefits of finding your model's most wrong predictions.mp4	MP4	59.3 MB
19. Discussing the benefits of finding your model's most wrong predictions.srt	SRT	9.41 KB
2. Getting helper functions ready and downloading data to model.mp4	MP4	131.54 MB
2. Getting helper functions ready and downloading data to model.srt	SRT	17.73 KB
20. Writing code to uncover our model's most wrong predictions.mp4	MP4	109.6 MB
20. Writing code to uncover our model's most wrong predictions.srt	SRT	17.03 KB
21. Plotting and visualising the samples our model got most wrong.mp4	MP4	125.49 MB
21. Plotting and visualising the samples our model got most wrong.srt	SRT	15.45 KB
22. Making predictions on and plotting our own custom images.mp4	MP4	108.3 MB
22. Making predictions on and plotting our own custom images.srt	SRT	14.61 KB
23. Transfer Learning in TensorFlow Part 3 challenge, exercises and extra-curriculum.html	HTML	2.28 KB
3. Outlining the model we're going to build and building a ModelCheckpoint callback.mp4	MP4	40.61 MB
3. Outlining the model we're going to build and building a ModelCheckpoint callback.srt	SRT	7.41 KB
4. Creating a data augmentation layer to use with our model.mp4	MP4	40.56 MB
4. Creating a data augmentation layer to use with our model.srt	SRT	6.25 KB
5. Creating a headless EfficientNetB0 model with data augmentation built in.mp4	MP4	80.41 MB
5. Creating a headless EfficientNetB0 model with data augmentation built in.srt	SRT	13.45 KB
6. Fitting and evaluating our biggest transfer learning model yet.mp4	MP4	70.15 MB
6. Fitting and evaluating our biggest transfer learning model yet.srt	SRT	11.43 KB
7. Unfreezing some layers in our base model to prepare for fine-tuning.mp4	MP4	100.07 MB
7. Unfreezing some layers in our base model to prepare for fine-tuning.srt	SRT	16.6 KB
8. Fine-tuning our feature extraction model and evaluating its performance.mp4	MP4	66.23 MB
8. Fine-tuning our feature extraction model and evaluating its performance.srt	SRT	11.87 KB
9. Saving and loading our trained model.mp4	MP4	57.41 MB
9. Saving and loading our trained model.srt	SRT	8.98 KB

9. Milestone Project 1 Food Vision Big™

1. Introduction to Milestone Project 1 Food Vision Big™.mp4	MP4	42.32 MB
1. Introduction to Milestone Project 1 Food Vision Big™.srt	SRT	9.17 KB
10. Turning on mixed precision training with TensorFlow.mp4	MP4	107.71 MB
10. Turning on mixed precision training with TensorFlow.srt	SRT	13.89 KB
11. Creating a feature extraction model capable of using mixed precision training.mp4	MP4	107.92 MB
11. Creating a feature extraction model capable of using mixed precision training.srt	SRT	17.41 KB
12. Checking to see if our model is using mixed precision training layer by layer.mp4	MP4	87.67 MB
12. Checking to see if our model is using mixed precision training layer by layer.srt	SRT	10.27 KB
13. Training and evaluating a feature extraction model (Food Vision Big™).mp4	MP4	89.02 MB
13. Training and evaluating a feature extraction model (Food Vision Big™).srt	SRT	14.12 KB
14. Introducing your Milestone Project 1 challenge build a model to beat DeepFood.mp4	MP4	89.12 MB
14. Introducing your Milestone Project 1 challenge build a model to beat DeepFood.srt	SRT	11.24 KB
15. Milestone Project 1 Food Vision Big™, exercises and extra-curriculum.html	HTML	2.32 KB
2. Making sure we have access to the right GPU for mixed precision training.mp4	MP4	88.15 MB
2. Making sure we have access to the right GPU for mixed precision training.srt	SRT	14.06 KB
3. Getting helper functions ready.mp4	MP4	31.09 MB
3. Getting helper functions ready.srt	SRT	3.94 KB
4. Introduction to TensorFlow Datasets (TFDS).mp4	MP4	116.84 MB
4. Introduction to TensorFlow Datasets (TFDS).srt	SRT	17.62 KB
5. Exploring and becoming one with the data (Food101 from TensorFlow Datasets).mp4	MP4	116.71 MB
5. Exploring and becoming one with the data (Food101 from TensorFlow Datasets).srt	SRT	22.34 KB
6. Creating a preprocessing function to prepare our data for modelling.mp4	MP4	132.19 MB
6. Creating a preprocessing function to prepare our data for modelling.srt	SRT	18.84 KB
7. Batching and preparing our datasets (to make them run fast).mp4	MP4	132.24 MB
7. Batching and preparing our datasets (to make them run fast).srt	SRT	19.22 KB
8. Exploring what happens when we batch and prefetch our data.mp4	MP4	63.82 MB
8. Exploring what happens when we batch and prefetch our data.srt	SRT	9.41 KB
9. Creating modelling callbacks for our feature extraction model.mp4	MP4	60.79 MB
9. Creating modelling callbacks for our feature extraction model.srt	SRT	9.84 KB

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