2023 Python for Deep Learning and Artificial Intelligence
Torrent Info
| Category | Other |
| Added | Saturday 8th July 2023 03:02:38 PM (3 years ago) |
| Size | 7.0 GB |
| Peers | 7 Peers (6 Seeders and 1 leechers) update |
| Downloaded | 3107 times |
| Uploader | tutsnode Thank You (0) Report Torrent 00/0 |
| Comments | None |
| Uploader Comments | None |
| Tags | English |
| Seeders | 6 |
| Leechers | 1 |
Torrent Screenshots
There are no images posted for this torrent.
NFO
None
| Filename | Size |
|---|---|
| 14. MobileNet Architecture Explained.mp4 | 121.3 MB |
| TutsNode.net.txt | 63 bytes |
| [TGx]Downloaded from torrentgalaxy.to .txt | 585 bytes |
| 0 | 688.4 KB |
| 3. Convolutional Filters.mp4 | 114.0 MB |
| 1 | 978.9 KB |
| 10. Data Visualization Part 2.mp4 | 107.3 MB |
| 2 | 767.2 KB |
| 15. EfficientNet Architecture Explained.mp4 | 104.3 MB |
| 3 | 713.5 KB |
| 1. Jupyter Notebook Introduction.mp4 | 103.1 MB |
| 4 | 939.7 KB |
| 5. Padding and Strides.mp4 | 102.3 MB |
| 5 | 683.9 KB |
| 11. AlexNet Architecture Explained.mp4 | 98.7 MB |
| 6 | 287.6 KB |
| 17. Online Prediction of Flowers Classes.mp4 | 96.9 MB |
| 7 | 75.5 KB |
| 6. Data Display in Subplots Matrix.mp4 | 89.2 MB |
| 8 | 796.9 KB |
| 4. Fashion MNIST Dataset Analysis.mp4 | 87.8 MB |
| 9 | 248.5 KB |
| 6. Pooling Layers.mp4 | 86.5 MB |
| 10 | 503.1 KB |
| 21. Load Model and Do the Prediction.mp4 | 83.4 MB |
| 11 | 610.1 KB |
| 12. Load Dataset for Baseline Classifier.mp4 | 82.9 MB |
| 12 | 62.2 KB |
| 2. Working Principle of CNN.mp4 | 80.2 MB |
| 13 | 811.9 KB |
| 5. What is Back Propagation.mp4 | 79.4 MB |
| 14 | 613.1 KB |
| 8. Discovering Overfitting - Early Stopping.mp4 | 77.5 MB |
| 15 | 467.3 KB |
| 4. Download Humans or Horses Dataset Part 2.mp4 | 76.0 MB |
| 16 | 998.4 KB |
| 1.1 python-for-deep-learning-and-ai.zip | 74.7 MB |
| 17 | 338.6 KB |
| 2. Introduction to TensorFlow Datasets (TFDS).mp4 | 74.6 MB |
| 18 | 362.4 KB |
| 5. Use of Image Data Generator.mp4 | 73.4 MB |
| 19 | 655.3 KB |
| 8. Other Types of Data Augmentation.mp4 | 73.3 MB |
| 20 | 674.5 KB |
| 7. Activation Function.mp4 | 72.7 MB |
| 21 | 353.1 KB |
| 10. LeNet-5 Architecture Explained.mp4 | 71.1 MB |
| 22 | 900.0 KB |
| 5. Sample Data Load with ImageDataGenerator for Augmentation.mp4 | 71.0 MB |
| 23 | 976.6 KB |
| 8. Matplotlib Introduction Part 2.mp4 | 70.1 MB |
| 24 | 926.5 KB |
| 15. How to Calculate Number of Parameters in CNN and FCN.mp4 | 68.7 MB |
| 25 | 332.6 KB |
| 12. GoogLeNet (Inception V1) Architecture Explained.mp4 | 68.4 MB |
| 26 | 626.2 KB |
| 2. Load Flowers Dataset for Classification.mp4 | 68.0 MB |
| 27 | 15.7 KB |
| 4. Feature Maps.mp4 | 66.9 MB |
| 28 | 125.5 KB |
| 13. Code Along in Python Part 4.mp4 | 66.7 MB |
| 29 | 336.7 KB |
| 7. Model Summary and Training.mp4 | 65.0 MB |
| 30 | 31.5 KB |
| 7. Matplotlib Introduction Part 1.mp4 | 64.8 MB |
| 31 | 244.9 KB |
| 3. Overview of NLP Tools.mp4 | 64.5 MB |
| 32 | 483.8 KB |
| 1. What is Convolutional Neural Network.mp4 | 64.2 MB |
| 33 | 823.6 KB |
| 7. Steps to Build Neural Network.mp4 | 64.1 MB |
| 34 | 942.6 KB |
| 13. Make CNN Model with VGG16 Transfer Learning.mp4 | 63.9 MB |
| 35 | 86.1 KB |
| 7. How to Calculate Number of Parameters in CNN.mp4 | 63.8 MB |
| 36 | 191.6 KB |
| 15. Train Any Model for Transfer Learning.mp4 | 63.3 MB |
| 37 | 744.7 KB |
| 3. Fashion MNIST Dataset Download.mp4 | 63.2 MB |
| 38 | 822.2 KB |
| 11. CNN Parameter Calculations Part 3.mp4 | 61.4 MB |
| 39 | 589.0 KB |
| 14. How to Calculate Size of Output Layers of CNN and MaxPool.mp4 | 61.3 MB |
| 40 | 695.2 KB |
| 14. Neural Network Model Building.mp4 | 60.9 MB |
| 41 | 130.8 KB |
| 8. Building CNN Model.mp4 | 60.7 MB |
| 42 | 332.8 KB |
| 10. Seaborn Introduction Part 2.mp4 | 59.7 MB |
| 43 | 285.6 KB |
| 11. Code Along in Python Part 2.mp4 | 59.1 MB |
| 44 | 871.7 KB |
| 12. Model Training.mp4 | 58.9 MB |
| 45 | 62.3 KB |
| 1. Transfer Learning Introduction.mp4 | 57.4 MB |
| 46 | 581.5 KB |
| 13. RestNet Architecture Explained.mp4 | 56.8 MB |
| 47 | 162.0 KB |
| 16. Model Training.mp4 | 56.3 MB |
| 48 | 744.3 KB |
| 3. Download Humans or Horses Dataset Part 1.mp4 | 56.2 MB |
| 49 | 868.8 KB |
| 6. Random Rotation Augmentation.mp4 | 55.8 MB |
| 50 | 182.2 KB |
| 9. CNN Architectures Comparison.mp4 | 55.6 MB |
| 51 | 447.7 KB |
| 2. Multi-Layer Perceptron.mp4 | 55.1 MB |
| 52 | 913.5 KB |
| 11. Store Data in Local Directory.mp4 | 53.1 MB |
| 53 | 952.4 KB |
| 7. CNN Introduction.mp4 | 53.0 MB |
| 54 | 992.1 KB |
| 14. Image Class Prediction.mp4 | 52.3 MB |
| 55 | 702.3 KB |
| 6. Optimizers in Deep Learning.mp4 | 52.1 MB |
| 56 | 949.9 KB |
| 5. Preparing Data with Image Data Generator.mp4 | 51.2 MB |
| 57 | 866.5 KB |
| 11. import VGG16 from Keras.mp4 | 51.0 MB |
| 58 | 1007.5 KB |
| 19. Prediction on Real-Life Data.mp4 | 50.9 MB |
| 59 | 62.1 KB |
| 9. Data Visualization Part 1.mp4 | 50.2 MB |
| 60 | 803.4 KB |
| 3. Download Flowers Data.mp4 | 50.0 MB |
| 61 | 1021.3 KB |
| 6. Pandas Introduction.mp4 | 49.6 MB |
| 62 | 453.1 KB |
| 15. Model Summary Explanation.mp4 | 48.8 MB |
| 63 | 208.9 KB |
| 4. Flowers Data Visualization.mp4 | 48.7 MB |
| 64 | 316.5 KB |
| 4. What is Data Augmentation [Theory].mp4 | 48.6 MB |
| 65 | 440.7 KB |
| 6. Baseline CNN Model Building.mp4 | 46.4 MB |
| 66 | 655.5 KB |
| 8. Baseline CNN Model Training.mp4 | 46.3 MB |
| 67 | 670.9 KB |
| 7. Random Shift Augmentation.mp4 | 45.9 MB |
| 68 | 61.9 KB |
| 8. Text Preprocessing.mp4 | 45.8 MB |
| 69 | 230.6 KB |
| 2. L1, L2 and Early Stopping Regularization.mp4 | 44.8 MB |
| 70 | 208.1 KB |
| 9. CNN Parameter Calculation.mp4 | 44.8 MB |
| 71 | 221.8 KB |
| 9. Model Save and Load for Prediction.mp4 | 44.7 MB |
| 72 | 322.6 KB |
| 12. Code Along in Python Part 3.mp4 | 44.1 MB |
| 73 | 925.3 KB |
| 1. Overview of Image Classification using CNNs.mp4 | 44.1 MB |
| 74 | 963.6 KB |
| 4. Unsupervised Learning.mp4 | 43.2 MB |
| 75 | 778.4 KB |
| 10. CNN Parameter Calculations Part 2.mp4 | 43.2 MB |
| 76 | 868.5 KB |
| 1. Introduction to Computer Vision with Deep Learning.mp4 | 43.0 MB |
| 77 | 33.9 KB |
| 1. What is Overfitting.mp4 | 42.8 MB |
| 78 | 244.6 KB |
| 3. How Dropout and Batch Normalization Prevents Overfitting.mp4 | 42.7 MB |
| 79 | 277.5 KB |
| 19. Regularized CNN Model Building and Training.mp4 | 42.4 MB |
| 80 | 564.3 KB |
| 10. TensorFlow TFDS and Cats vs Dogs Data Download.mp4 | 42.4 MB |
| 81 | 624.9 KB |
| 10. Pair Plot.mp4 | 41.9 MB |
| 82 | 64.8 KB |
| 13. Building Baseline CNN Classifier.mp4 | 41.6 MB |
| 83 | 392.7 KB |
| 9. Train Model with TFDS Data Without Saving Locally Part 1.mp4 | 41.3 MB |
| 84 | 718.5 KB |
| 16. Save and Load Model with Class Names.mp4 | 40.4 MB |
| 85 | 630.1 KB |
| 4. Activation Function.mp4 | 40.3 MB |
| 86 | 689.7 KB |
| 4. Numpy Introduction Part 1.mp4 | 40.1 MB |
| 87 | 930.0 KB |
| 16. Model Training and Layers Analysis.mp4 | 39.9 MB |
| 88 | 95.4 KB |
| 2. What are Key NLP Techniques.mp4 | 39.6 MB |
| 89 | 434.7 KB |
| 10. Train Model with TFDS Data Without Saving Locally Part 2.mp4 | 38.5 MB |
| 90 | 561.8 KB |
| 6. L2 Regularization.mp4 | 38.3 MB |
| 91 | 713.2 KB |
| 1. Machine Learning Process Introduction.mp4 | 38.0 MB |
| 92 | 19.6 KB |
| 2. Python Introduction Part 2.mp4 | 37.8 MB |
| 93 | 176.4 KB |
| 3. Support Vector Machine - SVM.mp4 | 37.7 MB |
| 94 | 345.2 KB |
| 12. Import Neural Networks APIs.mp4 | 37.1 MB |
| 95 | 967.8 KB |
| 6. Deep Neural Network Model Building.mp4 | 36.5 MB |
| 96 | 477.4 KB |
| 11. Data Preprocessing.mp4 | 36.4 MB |
| 97 | 638.7 KB |
| 5. Numpy Introduction Part 2.mp4 | 36.3 MB |
| 98 | 713.4 KB |
| 12. TF-IDF Vectorization.mp4 | 34.7 MB |
| 99 | 295.8 KB |
| 3. Python Introduction Part 3.mp4 | 34.7 MB |
| 100 | 353.8 KB |
| 2. Logistic Regression.mp4 | 34.4 MB |
| 101 | 583.3 KB |
| 10. Code Along in Python Part 1.mp4 | 34.4 MB |
| 102 | 657.8 KB |
| 9. Feature Engineering.mp4 | 33.7 MB |
| 103 | 302.4 KB |
| 1. Python Introduction Part 1.mp4 | 33.6 MB |
| 104 | 458.0 KB |
| 7. What is Neural Network.mp4 | 33.2 MB |
| 105 | 798.5 KB |
| 9. All Types of Augmentation at Once.mp4 | 32.7 MB |
| 106 | 348.6 KB |
| 8. Dropout.mp4 | 32.4 MB |
| 107 | 652.8 KB |
| 13. Model Load and Save.mp4 | 32.1 MB |
| 108 | 941.6 KB |
| 1. Classical Machine Learning Introduction.mp4 | 32.0 MB |
| 109 | 19.4 KB |
| 10. Deep Learning Tools.mp4 | 31.8 MB |
| 110 | 227.7 KB |
| 8. Model Evaluation.mp4 | 31.5 MB |
| 111 | 505.4 KB |
| 9. Seaborn Introduction Part 1.mp4 | 30.6 MB |
| 112 | 425.1 KB |
| 6. What is Deep Learning and ML.mp4 | 30.2 MB |
| 113 | 812.3 KB |
| 9. Application of Deep Learning.mp4 | 28.6 MB |
| 114 | 398.0 KB |
| 2. 5 Steps of Computer Vision Model Building.mp4 | 27.7 MB |
| 115 | 332.2 KB |
| 5. Bag of Words - The Simples Word Embedding Technique.mp4 | 27.3 MB |
| 116 | 704.4 KB |
| 8. Customer Churn Dataset Loading.mp4 | 26.0 MB |
| 117 | 1023.5 KB |
| 17. Model Training and Validation Accuracy Plot.mp4 | 26.0 MB |
| 118 | 28.2 KB |
| 5. Train Test Split for Data.mp4 | 25.8 MB |
| 119 | 185.4 KB |
| 12. Data Augmentation for Training.mp4 | 25.6 MB |
| 120 | 381.2 KB |
| 3. Supervised Learning.mp4 | 25.5 MB |
| 121 | 468.2 KB |
| 20. Training Log Analysis.mp4 | 25.5 MB |
| 122 | 470.0 KB |
| 4. Decision Tree.mp4 | 25.5 MB |
| 123 | 506.5 KB |
| 8. How Deep Learning Process Works.mp4 | 23.9 MB |
| 124 | 55.6 KB |
| 18. Model Save and Load.mp4 | 23.6 MB |
| 125 | 384.4 KB |
| 14. Model Training for Better Accuracy.mp4 | 23.3 MB |
| 126 | 668.0 KB |
| 1. Introduction to NLP.mp4 | 22.6 MB |
| 127 | 457.2 KB |
| 13. Model Evaluation and Prediction on Real Data.mp4 | 22.3 MB |
| 128 | 753.1 KB |
| 14. Model Load and Store.mp4 | 22.1 MB |
| 129 | 954.0 KB |
| 11. MLops with AWS.mp4 | 21.6 MB |
| 130 | 367.5 KB |
| 13. How to Get Input Shape and Class Weights.mp4 | 21.2 MB |
| 131 | 825.0 KB |
| 1. What is Neuron.mp4 | 20.9 MB |
| 132 | 149.6 KB |
| 6. Term Frequency - Inverse Document Frequency (TF-IDF).mp4 | 20.0 MB |
| 133 | 999.8 KB |
| 2. Types of Machine Learning.mp4 | 19.3 MB |
| 134 | 731.2 KB |
| 4. Common Challenges in NLP.mp4 | 19.1 MB |
| 135 | 887.0 KB |
| 7. L1 Regularization.mp4 | 18.7 MB |
| 136 | 265.9 KB |
| 7. Load Spam Dataset.mp4 | 18.6 MB |
| 137 | 449.8 KB |
| 18. Building Dataset for Regularized CNN.mp4 | 17.5 MB |
| 138 | 507.3 KB |
| 5. Random Forest.mp4 | 17.5 MB |
| 139 | 532.8 KB |
| 5. Reinforcement Learning.mp4 | 16.3 MB |
| 140 | 747.7 KB |
| 17. Model Evaluation.mp4 | 16.1 MB |
| 141 | 906.6 KB |
| 22. CNN Model Visualization.mp4 | 14.3 MB |
| 142 | 705.5 KB |
| 3. Shallow vs Deep Neural Networks.mp4 | 13.8 MB |
| 143 | 158.5 KB |
| 9. ROC-AUC Curve.mp4 | 13.5 MB |
| 144 | 554.6 KB |
| 11. Train Test Split.mp4 | 8.7 MB |
Comments
Similar torrents
| Torrent name | ||||||||
|---|---|---|---|---|---|---|---|---|
 |
2023-07-01 15:47:53 |
0 |
44.0 MB |
0 |
1 |
1 |
||
|
FreeCourseWeb in
Books
::
EBooks
|
|
2023-12-25 17:52:22 |
0 |
17.6 MB |
0 |
1 |
0 |
|
|
2023-06-02 18:12:33 |
0 |
11.7 MB |
0 |
1 |
1 |
||
|
SunRiseZone in
Other
::
Other
|
|
2023-06-02 09:01:31 |
0 |
24.0 MB |
0 |
0 |
3 |
|
|
2023-06-02 22:47:41 |
0 |
13.2 MB |
0 |
0 |
1 |
||
|
indexFroggy in
Books
::
EBooks
|
|
2023-11-09 08:20:49 |
0 |
53.7 MB |
0 |
7 |
1 |
|
|
SunRiseZone in
Other
::
Other
|
|
2023-07-02 04:39:44 |
0 |
306.4 MB |
0 |
1 |
0 |
|
|
2023-10-24 15:53:53 |
0 |
3.0 GB |
0 |
0 |
0 |
||
|
freecoursewb in
Other
::
Other
|
|
2023-06-02 04:09:32 |
0 |
106.9 MB |
0 |
0 |
0 |
|
|
freecoursewb in
Other
::
Other
|
|
2023-06-01 20:35:52 |
0 |
3.0 GB |
0 |
0 |
12 |
|