zhongziso
搜索
zhongziso
首页
首页
功能
磁力转BT
BT转磁力
关于
使用教程
免责声明
磁力助手
[FreeCourseSite.com] Udemy - Introduction to Machine Learning & Deep Learning in Python
magnet:?xt=urn:btih:02273c6646e727e4871a7c0002893ed0fb71aa92&dn=[FreeCourseSite.com] Udemy - Introduction to Machine Learning & Deep Learning in Python
磁力链接详情
文件列表详情
02273c6646e727e4871a7c0002893ed0fb71aa92
infohash:
140
文件数量
1.67 GB
文件大小
2019-12-11 12:45
创建日期
2024-10-5 18:14
最后访问
相关分词
FreeCourseSite
com
Udemy
-
Introduction
to
Machine
Learning
&
Deep
Learning
in
Python
1. Introduction/1. Introduction.mp4 3.48 MB
1. Introduction/2. Introduction to machine learning.mp4 8.05 MB
10. Boosting/1. Boosting introduction - basics.mp4 8.39 MB
10. Boosting/2. Boosting introduction - illustration.mp4 8.17 MB
10. Boosting/3. Boosting introduction - equations.mp4 13.71 MB
10. Boosting/4. Boosting introduction - final formula.mp4 13.01 MB
10. Boosting/5. Boosting implementation I - iris dataset.mp4 12.33 MB
10. Boosting/6. Boosting implementation II -tuning.mp4 10.35 MB
10. Boosting/7. Boosting vs. bagging.mp4 5.21 MB
11. Clustering/1. Principal component anlysis introduction.mp4 8.58 MB
11. Clustering/10. Hierarchical clustering example.mp4 11.96 MB
11. Clustering/2. Principal component analysis example.mp4 14 MB
11. Clustering/3. K-means clustering introduction I.mp4 13.67 MB
11. Clustering/4. K-means clustering introduction II.mp4 9.47 MB
11. Clustering/5. K-means clustering example.mp4 9.43 MB
11. Clustering/6. K-means clustering - text clustering.mp4 18.86 MB
11. Clustering/7. DBSCAN introduction.mp4 11.05 MB
11. Clustering/8. DBSCAN example.mp4 7.88 MB
11. Clustering/9. Hierarchical clustering introduction.mp4 13.66 MB
12. Neural Networks/11. Feedforward neural networks.mp4 18.42 MB
12. Neural Networks/12. Optimization - cost function.mp4 25.89 MB
12. Neural Networks/13. Simplified feedforward network.mp4 19.42 MB
12. Neural Networks/14. Feedforward neural network topology.mp4 14.73 MB
12. Neural Networks/15. The learning algorithm.mp4 13.26 MB
12. Neural Networks/16. Error calculation.mp4 13.74 MB
12. Neural Networks/17. Gradient calculation I - output layer.mp4 20.28 MB
12. Neural Networks/18. Gradient calculation II - hidden layer.mp4 9.18 MB
12. Neural Networks/19. Backpropagation.mp4 12.67 MB
12. Neural Networks/2. Axons and neurons in the human brain.mp4 19.24 MB
12. Neural Networks/20. Backpropagation II.mp4 4.68 MB
12. Neural Networks/21. Applications of neural networks I - character recognition.mp4 8.78 MB
12. Neural Networks/22. Applications of neural networks II - stock market forecast.mp4 9.53 MB
12. Neural Networks/23. Deep learning.mp4 9.47 MB
12. Neural Networks/25. Building networks.mp4 12.75 MB
12. Neural Networks/26. Building networks II.mp4 12.02 MB
12. Neural Networks/27. Handling datasets.mp4 6.21 MB
12. Neural Networks/28. Neural network example I - XOR problem.mp4 17.61 MB
12. Neural Networks/29. Neural network example II - iris dataset.mp4 35.59 MB
12. Neural Networks/3. Modeling human brain.mp4 16.17 MB
12. Neural Networks/4. Learning paradigms.mp4 6.51 MB
12. Neural Networks/5. Artificial neurons - the model.mp4 16.55 MB
12. Neural Networks/6. Artificial neurons - activation functions.mp4 14.24 MB
12. Neural Networks/7. Artificial neurons - an example.mp4 11.37 MB
12. Neural Networks/8. Neural networks - the big picture.mp4 10.78 MB
12. Neural Networks/9. Applications of neural networks.mp4 5.23 MB
13. Machine Learning in Finance/1. Stock market basics.mp4 5.63 MB
13. Machine Learning in Finance/2. Fetching data from Yahoo Finance.mp4 7.96 MB
13. Machine Learning in Finance/3. Predicting stock prices logistic regression.mp4 10.76 MB
13. Machine Learning in Finance/4. Predicting stock prices k-nearest neighbor.mp4 7.1 MB
13. Machine Learning in Finance/5. Predicting stock prices support vector machine.mp4 8.71 MB
13. Machine Learning in Finance/6. Predicting stock prices - conclusion.mp4 3.51 MB
14. Computer Vision - Face Detection/1. Computer vision introduction.mp4 5.76 MB
14. Computer Vision - Face Detection/10. Face detection implementation IV - tuning the parameters.mp4 8.73 MB
14. Computer Vision - Face Detection/2. Viola-Jones algorithm.mp4 20.94 MB
14. Computer Vision - Face Detection/3. Haar-features.mp4 12.64 MB
14. Computer Vision - Face Detection/4. Integral images.mp4 9.58 MB
14. Computer Vision - Face Detection/5. Boosting in computer vision.mp4 12.32 MB
14. Computer Vision - Face Detection/6. Cascading.mp4 6.23 MB
14. Computer Vision - Face Detection/7. Face detection implementation I - installing OpenCV.mp4 10.56 MB
14. Computer Vision - Face Detection/8. Face detection implementation II - CascadeClassifier.mp4 15.92 MB
14. Computer Vision - Face Detection/9. Face detection implementation III - CascadeClassifier parameters.mp4 8.6 MB
15. Deep Learning/1. Types of neural networks.mp4 5.49 MB
16. Deep Neural Networks/1. Deep neural networks.mp4 7.65 MB
16. Deep Neural Networks/11. Multiclass classification implementation I.mp4 11.1 MB
16. Deep Neural Networks/12. Multiclass classification implementation II.mp4 10.31 MB
16. Deep Neural Networks/2. Activation functions revisited.mp4 15.42 MB
16. Deep Neural Networks/3. Loss functions.mp4 10.39 MB
16. Deep Neural Networks/4. Gradient descent stochastic gradient descent.mp4 12.26 MB
16. Deep Neural Networks/5. Hyperparameters.mp4 8.26 MB
16. Deep Neural Networks/7. Deep neural network implementation I.mp4 15.09 MB
16. Deep Neural Networks/8. Deep neural network implementation II.mp4 15.81 MB
16. Deep Neural Networks/9. Deep neural network implementation III.mp4 18.4 MB
17. Convolutional Neural Networks/10. Handwritten digit classification I.mp4 16.48 MB
17. Convolutional Neural Networks/11. Handwritten digit classification II.mp4 15.65 MB
17. Convolutional Neural Networks/12. Handwritten digit classification III.mp4 10.44 MB
17. Convolutional Neural Networks/2. Convolutional neural networks basics.mp4 9.58 MB
17. Convolutional Neural Networks/3. Feature selection.mp4 6.95 MB
17. Convolutional Neural Networks/4. Convolutional neural networks - kernel.mp4 6.34 MB
17. Convolutional Neural Networks/5. Convolutional neural networks - kernel II.mp4 7.79 MB
17. Convolutional Neural Networks/6. Convolutional neural networks - pooling.mp4 9.85 MB
17. Convolutional Neural Networks/7. Convolutional neural networks - flattening.mp4 8.41 MB
17. Convolutional Neural Networks/8. Convolutional neural networks - illustration.mp4 6.02 MB
18. Recurrent Neural Networks/10. Stock price prediction example III.mp4 4.98 MB
18. Recurrent Neural Networks/11. Stock price prediction example IV.mp4 14.55 MB
18. Recurrent Neural Networks/12. Stock price prediction example V.mp4 6.74 MB
18. Recurrent Neural Networks/13. Stock price prediction example VI.mp4 15.2 MB
18. Recurrent Neural Networks/14. Stock price prediction example VII.mp4 7.21 MB
18. Recurrent Neural Networks/2. Why do recurrent neural networks are important.mp4 7.52 MB
18. Recurrent Neural Networks/3. Recurrent neural networks basics.mp4 12.89 MB
18. Recurrent Neural Networks/4. Vanishing and exploding gradients problem.mp4 19.63 MB
18. Recurrent Neural Networks/5. Long-short term memory (LTSM) model.mp4 17.03 MB
18. Recurrent Neural Networks/6. Gated recurrent units (GRUs).mp4 5.03 MB
18. Recurrent Neural Networks/8. Stock price prediction example I.mp4 11.09 MB
18. Recurrent Neural Networks/9. Stock price prediction example II.mp4 18.37 MB
2. Installations/1. Installing Anaconda.mp4 4.32 MB
2. Installations/2. Installing Spyder.mp4 2.8 MB
2. Installations/3. Installing Keras and TensorFlow.mp4 5.95 MB
3. Linear Regression/1. Linear regression introduction.mp4 26.43 MB
3. Linear Regression/2. Linear regression theory - optimization.mp4 42.28 MB
3. Linear Regression/3. Linear regression theory - gradient descent.mp4 11.1 MB
3. Linear Regression/4. Linear regression implementation I.mp4 16.69 MB
3. Linear Regression/5. Linear regression implementation II.mp4 8.78 MB
4. Logistic Regression/1. Logistic regression introduction.mp4 17.63 MB
4. Logistic Regression/2. Logistic regression introduction II.mp4 6.67 MB
4. Logistic Regression/3. Logistic regression example I - sigmoid function.mp4 13.04 MB
4. Logistic Regression/4. Logistic regression example II- credit scoring.mp4 21.33 MB
4. Logistic Regression/5. Logistic regression example III - credit scoring.mp4 10.87 MB
4. Logistic Regression/6. Cross validation introduction.mp4 11.72 MB
4. Logistic Regression/7. Cross validation example.mp4 4.15 MB
5. K-Nearest Neighbor Classifier/1. K-nearest neighbor introduction.mp4 9.48 MB
5. K-Nearest Neighbor Classifier/2. K-nearest neighbor introduction - lazy learning.mp4 8.11 MB
5. K-Nearest Neighbor Classifier/3. K-nearest neighbor introduction - Euclidean-distance.mp4 8.61 MB
5. K-Nearest Neighbor Classifier/5. K-nearest neighbor implementation I.mp4 6.95 MB
5. K-Nearest Neighbor Classifier/6. K-nearest neighbor implementation II.mp4 9.96 MB
5. K-Nearest Neighbor Classifier/7. K-nearest neighbor implementation III.mp4 7.93 MB
6. Naive Bayes Classifier/1. Naive Bayes classifier introduction I.mp4 17.44 MB
6. Naive Bayes Classifier/2. Naive Bayes classifier introduction II - illustration.mp4 8.43 MB
6. Naive Bayes Classifier/3. Naive Bayes classifier implementation.mp4 8 MB
6. Naive Bayes Classifier/5. Text clustering - basics.mp4 22.12 MB
6. Naive Bayes Classifier/6. Text clustering - inverse document frequency (TF-IDF).mp4 10.02 MB
6. Naive Bayes Classifier/7. Naive Bayes example - clustering news.mp4 23.33 MB
7. Support Vector Machine (SVM)/1. Support vector machine introduction I - linear case.mp4 20.76 MB
7. Support Vector Machine (SVM)/2. Support vector machine introduction II - non-linear case.mp4 17.22 MB
7. Support Vector Machine (SVM)/3. Support vector machine introduction III - kernels.mp4 9.9 MB
7. Support Vector Machine (SVM)/4. Support vector machine example I - simple.mp4 10.48 MB
7. Support Vector Machine (SVM)/5. Support vector machine example II - iris dataset.mp4 21.7 MB
7. Support Vector Machine (SVM)/6. Support vector machine example III - digit recognition.mp4 16.43 MB
8. Decision Trees/1. Decision trees introduction - basics.mp4 11.73 MB
8. Decision Trees/2. Decision trees introduction - entropy.mp4 19.29 MB
8. Decision Trees/3. Decision trees introduction - information gain.mp4 46.96 MB
8. Decision Trees/4. Decision trees introduction - pros and cons.mp4 4.19 MB
8. Decision Trees/5. Decision trees implementation.mp4 13.6 MB
8. Decision Trees/6. Decision trees implementation II.mp4 6.66 MB
8. Decision Trees/7. The Gini-index approach.mp4 18.75 MB
9. Random Forest Classifier/1. Pruning introduction.mp4 9.83 MB
9. Random Forest Classifier/2. Bagging introduction.mp4 11.72 MB
9. Random Forest Classifier/3. Random forest classifier introduction.mp4 8.72 MB
9. Random Forest Classifier/4. Random forests example I - iris dataset.mp4 11.36 MB
9. Random Forest Classifier/5. Random forests example II - credit scoring.mp4 4.21 MB
9. Random Forest Classifier/6. Random forests example III - parameter tuning.mp4 9.19 MB
其他位置