2014斯坦福大学机器学习mkv视频

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文档个数：585个文档
下载次数：38次
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收录时间：2017-06-09
最近下载：2024-01-05
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文档列表

1 - 1 - Welcome (7 min).mkv 12.3 MB
1 - 2 - What is Machine Learning_ (7 min).mkv 9.7 MB
1 - 3 - Supervised Learning (12 min).mkv 13.9 MB
1 - 4 - Unsupervised Learning (14 min).mkv 17.2 MB
10 - 1 - Deciding What to Try Next (6 min).mkv 7.1 MB
10 - 2 - Evaluating a Hypothesis (8 min).mkv 8.8 MB
10 - 3 - Model Selection and Train_Validation_Test Sets (12 min).mkv 15.6 MB
10 - 4 - Diagnosing Bias vs. Variance (8 min).mkv 9.3 MB
10 - 5 - Regularization and Bias_Variance (11 min).mkv 13.0 MB
10 - 6 - Learning Curves (12 min).mkv 13.4 MB
10 - 7 - Deciding What to Do Next Revisited (7 min).mkv 8.5 MB
11 - 1 - Prioritizing What to Work On (10 min).mkv 11.6 MB
11 - 2 - Error Analysis (13 min).mkv 16.0 MB
11 - 3 - Error Metrics for Skewed Classes (12 min).mkv 13.7 MB
11 - 4 - Trading Off Precision and Recall (14 min).mkv 16.5 MB
11 - 5 - Data For Machine Learning (11 min).mkv 13.3 MB
12 - 1 - Optimization Objective (15 min).mkv 17.2 MB
12 - 2 - Large Margin Intuition (11 min).mkv 12.2 MB
12 - 3 - Mathematics Behind Large Margin Classification (Optional) (20 min).mkv 22.6 MB
12 - 4 - Kernels I (16 min).mkv 18.2 MB
12 - 5 - Kernels II (16 min).mkv 18.0 MB
12 - 6 - Using An SVM (21 min).mkv 24.8 MB
13 - 1 - Unsupervised Learning_ Introduction (3 min).mkv 3.9 MB
13 - 2 - K-Means Algorithm (13 min).mkv 14.3 MB
13 - 3 - Optimization Objective (7 min)(1).mkv 8.4 MB
13 - 3 - Optimization Objective (7 min).mkv 8.4 MB
13 - 4 - Random Initialization (8 min).mkv 9.0 MB
13 - 5 - Choosing the Number of Clusters (8 min).mkv 9.7 MB
14 - 1 - Motivation I_ Data Compression (10 min).mkv 14.8 MB
14 - 2 - Motivation II_ Visualization (6 min).mkv 6.5 MB
14 - 3 - Principal Component Analysis Problem Formulation (9 min).mkv 10.8 MB
14 - 4 - Principal Component Analysis Algorithm (15 min).mkv 18.4 MB
14 - 5 - Choosing the Number of Principal Components (11 min).mkv 12.2 MB
14 - 6 - Reconstruction from Compressed Representation (4 min).mkv 5.2 MB
14 - 7 - Advice for Applying PCA (13 min).mkv 15.2 MB
15 - 1 - Problem Motivation (8 min).mkv 8.6 MB
15 - 2 - Gaussian Distribution (10 min).mkv 12.1 MB
15 - 3 - Algorithm (12 min).mkv 14.4 MB
15 - 4 - Developing and Evaluating an Anomaly Detection System (13 min).mkv 15.7 MB
15 - 5 - Anomaly Detection vs. Supervised Learning (8 min).mkv 9.6 MB
15 - 6 - Choosing What Features to Use (12 min).mkv 14.6 MB
15 - 7 - Multivariate Gaussian Distribution (Optional) (14 min).mkv 16.5 MB
15 - 8 - Anomaly Detection using the Multivariate Gaussian Distribution (Optional) (14 min).mkv 16.9 MB
16 - 1 - Problem Formulation (8 min).mkv 11.1 MB
16 - 2 - Content Based Recommendations (15 min).mkv 17.5 MB
16 - 3 - Collaborative Filtering (10 min).mkv 12.2 MB
16 - 4 - Collaborative Filtering Algorithm (9 min).mkv 10.7 MB
16 - 5 - Vectorization_ Low Rank Matrix Factorization (8 min).mkv 10.0 MB
16 - 6 - Implementational Detail_ Mean Normalization (9 min).mkv 10.0 MB
17 - 1 - Learning With Large Datasets (6 min).mkv 6.7 MB
17 - 2 - Stochastic Gradient Descent (13 min).mkv 15.9 MB
17 - 3 - Mini-Batch Gradient Descent (6 min).mkv 7.6 MB
17 - 4 - Stochastic Gradient Descent Convergence (12 min).mkv 13.8 MB
17 - 5 - Online Learning (13 min).mkv 15.4 MB
17 - 6 - Map Reduce and Data Parallelism (14 min).mkv 16.6 MB
18 - 1 - Problem Description and Pipeline (7 min).mkv 8.2 MB
18 - 2 - Sliding Windows (15 min).mkv 17.1 MB
18 - 3 - Getting Lots of Data and Artificial Data (16 min).mkv 19.5 MB
18 - 4 - Ceiling Analysis_ What Part of the Pipeline to Work on Next (14 min).mkv 16.7 MB
19 - 1 - Summary and Thank You (5 min).mkv 6.3 MB
2 - 1 - Model Representation (8 min).mkv 9.3 MB
2 - 2 - Cost Function (8 min).mkv 9.3 MB
2 - 3 - Cost Function - Intuition I (11 min).mkv 12.6 MB
2 - 4 - Cost Function - Intuition II (9 min).mkv 11.8 MB
2 - 5 - Gradient Descent (11 min).mkv 14.0 MB
2 - 6 - Gradient Descent Intuition (12 min).mkv 13.5 MB
2 - 7 - GradientDescentForLinearRegression (6 min).mkv 12.6 MB
2 - 8 - What_'s Next (6 min).mkv 6.3 MB
3 - 1 - Matrices and Vectors (9 min).mkv 9.9 MB
3 - 2 - Addition and Scalar Multiplication (7 min).mkv 7.7 MB
3 - 3 - Matrix Vector Multiplication (14 min).mkv 15.5 MB
3 - 4 - Matrix Matrix Multiplication (11 min).mkv 13.0 MB
3 - 5 - Matrix Multiplication Properties (9 min).mkv 10.1 MB
3 - 6 - Inverse and Transpose (11 min).mkv 13.3 MB
4 - 1 - Multiple Features (8 min).mkv 9.1 MB
4 - 2 - Gradient Descent for Multiple Variables (5 min).mkv 6.0 MB
4 - 3 - Gradient Descent in Practice I - Feature Scaling (9 min).mkv 9.8 MB
4 - 4 - Gradient Descent in Practice II - Learning Rate (9 min).mkv 9.6 MB
4 - 5 - Features and Polynomial Regression (8 min).mkv 8.5 MB
4 - 6 - Normal Equation (16 min).mkv 17.7 MB
4 - 7 - Normal Equation Noninvertibility (Optional) (6 min).mkv 6.5 MB
5 - 1 - Basic Operations (14 min).mkv 18.4 MB
5 - 2 - Moving Data Around (16 min).mkv 21.5 MB
5 - 3 - Computing on Data (13 min).mkv 15.8 MB
5 - 4 - Plotting Data (10 min).mkv 13.8 MB
5 - 5 - Control Statements_ for, while, if statements (13 min).mkv 17.1 MB
5 - 6 - Vectorization (14 min).mkv 16.6 MB
5 - 7 - Working on and Submitting Programming Exercises (4 min).mkv 5.7 MB
6 - 1 - Classification (8 min).mkv 9.1 MB
6 - 2 - Hypothesis Representation (7 min).mkv 8.6 MB
6 - 3 - Decision Boundary (15 min).mkv 17.3 MB
6 - 4 - Cost Function (11 min).mkv 13.5 MB
6 - 5 - Simplified Cost Function and Gradient Descent (10 min).mkv 12.4 MB
6 - 6 - Advanced Optimization (14 min).mkv 18.8 MB
6 - 7 - Multiclass Classification_ One-vs-all (6 min).mkv 7.2 MB
7 - 1 - The Problem of Overfitting (10 min).mkv 11.5 MB
7 - 2 - Cost Function (10 min).mkv 12.0 MB
7 - 3 - Regularized Linear Regression (11 min).mkv 12.4 MB
7 - 4 - Regularized Logistic Regression (9 min).mkv 11.3 MB
8 - 1 - Non-linear Hypotheses (10 min).mkv 11.3 MB
8 - 2 - Neurons and the Brain (8 min).mkv 10.2 MB
8 - 3 - Model Representation I (12 min).mkv 14.0 MB
8 - 4 - Model Representation II (12 min).mkv 13.9 MB
8 - 5 - Examples and Intuitions I (7 min).mkv 8.2 MB
8 - 6 - Examples and Intuitions II (10 min).mkv 14.5 MB
8 - 7 - Multiclass Classification (4 min).mkv 5.0 MB
9 - 1 - Cost Function (7 min).mkv 7.9 MB
9 - 2 - Backpropagation Algorithm (12 min).mkv 14.4 MB
9 - 3 - Backpropagation Intuition (13 min).mkv 16.0 MB
9 - 4 - Implementation Note_ Unrolling Parameters (8 min).mkv 9.7 MB
9 - 5 - Gradient Checking (12 min).mkv 14.0 MB
9 - 6 - Random Initialization (7 min).mkv 7.8 MB
9 - 7 - Putting It Together (14 min).mkv 16.9 MB
9 - 8 - Autonomous Driving (7 min).mkv 15.5 MB
pdf/Lecture1.pdf 3.5 MB
pdf/Lecture10.pdf 1.6 MB
pdf/Lecture11.pdf 509.6 kB
pdf/Lecture12.pdf 2.4 MB
pdf/Lecture13.pdf 2.3 MB
pdf/Lecture14.pdf 1.7 MB
pdf/Lecture15.pdf 3.5 MB
pdf/Lecture16.pdf 1.5 MB
pdf/Lecture17.pdf 2.1 MB
pdf/Lecture18.pdf 2.1 MB
pdf/Lecture2.pdf 3.0 MB
pdf/Lecture3.pdf 1.9 MB
pdf/Lecture4.pdf 1.8 MB
pdf/Lecture5.pdf 248.2 kB
pdf/Lecture6.pdf 2.2 MB
pdf/Lecture7.pdf 2.5 MB
pdf/Lecture8.pdf 5.2 MB
pdf/Lecture9.pdf 3.5 MB
ppt/Lecture1.pptx 4.2 MB
ppt/Lecture10.pptx 3.5 MB
ppt/Lecture11.pptx 2.0 MB
ppt/Lecture12.pptx 5.6 MB
ppt/Lecture13.pptx 2.9 MB
ppt/Lecture14.pptx 3.8 MB
ppt/Lecture15.pptx 6.3 MB
ppt/Lecture16.pptx 3.8 MB
ppt/Lecture17.pptx 4.0 MB
ppt/Lecture18.pptx 6.4 MB
ppt/Lecture2.pptx 5.6 MB
ppt/Lecture3.pptx 5.2 MB
ppt/Lecture4.pptx 4.6 MB
ppt/Lecture5.pptx 417.1 kB
ppt/Lecture6.pptx 4.0 MB
ppt/Lecture7.pptx 2.7 MB
ppt/Lecture8.pptx 42.3 MB
ppt/Lecture9.pptx 5.2 MB
推荐播放器/PotPlayer_1.6.51270.zip 20.1 MB
教程和笔记/Stanford-Machine-Learning-Course-master/Anomaly Detection and Recommender Systems/ex8.pdf 270.9 kB
教程和笔记/Stanford-Machine-Learning-Course-master/Anomaly Detection and Recommender Systems/mlclass-ex8/checkCostFunction.m 1.6 kB
教程和笔记/Stanford-Machine-Learning-Course-master/Anomaly Detection and Recommender Systems/mlclass-ex8/cofiCostFunc.m 2.2 kB
教程和笔记/Stanford-Machine-Learning-Course-master/Anomaly Detection and Recommender Systems/mlclass-ex8/computeNumericalGradient.m 1.1 kB
教程和笔记/Stanford-Machine-Learning-Course-master/Anomaly Detection and Recommender Systems/mlclass-ex8/estimateGaussian.m 986 Bytes
教程和笔记/Stanford-Machine-Learning-Course-master/Anomaly Detection and Recommender Systems/mlclass-ex8/ex8.m 3.8 kB
教程和笔记/Stanford-Machine-Learning-Course-master/Anomaly Detection and Recommender Systems/mlclass-ex8/ex8_cofi.m 7.1 kB
教程和笔记/Stanford-Machine-Learning-Course-master/Anomaly Detection and Recommender Systems/mlclass-ex8/ex8_movieParams.mat 201.2 kB
教程和笔记/Stanford-Machine-Learning-Course-master/Anomaly Detection and Recommender Systems/mlclass-ex8/ex8_movies.mat 223.4 kB
教程和笔记/Stanford-Machine-Learning-Course-master/Anomaly Detection and Recommender Systems/mlclass-ex8/ex8data1.mat 9.5 kB
教程和笔记/Stanford-Machine-Learning-Course-master/Anomaly Detection and Recommender Systems/mlclass-ex8/ex8data2.mat 93.5 kB
教程和笔记/Stanford-Machine-Learning-Course-master/Anomaly Detection and Recommender Systems/mlclass-ex8/fmincg.m 8.7 kB
教程和笔记/Stanford-Machine-Learning-Course-master/Anomaly Detection and Recommender Systems/mlclass-ex8/loadMovieList.m 651 Bytes
教程和笔记/Stanford-Machine-Learning-Course-master/Anomaly Detection and Recommender Systems/mlclass-ex8/movie_ids.txt 48.4 kB
教程和笔记/Stanford-Machine-Learning-Course-master/Anomaly Detection and Recommender Systems/mlclass-ex8/multivariateGaussian.m 829 Bytes
教程和笔记/Stanford-Machine-Learning-Course-master/Anomaly Detection and Recommender Systems/mlclass-ex8/normalizeRatings.m 460 Bytes
教程和笔记/Stanford-Machine-Learning-Course-master/Anomaly Detection and Recommender Systems/mlclass-ex8/octave-core 40.5 MB
教程和笔记/Stanford-Machine-Learning-Course-master/Anomaly Detection and Recommender Systems/mlclass-ex8/selectThreshold.m 1.5 kB
教程和笔记/Stanford-Machine-Learning-Course-master/Anomaly Detection and Recommender Systems/mlclass-ex8/submit.m 9.3 kB
教程和笔记/Stanford-Machine-Learning-Course-master/Anomaly Detection and Recommender Systems/mlclass-ex8/submitWeb.m 10.9 kB
教程和笔记/Stanford-Machine-Learning-Course-master/Anomaly Detection and Recommender Systems/mlclass-ex8/visualizeFit.m 582 Bytes
教程和笔记/Stanford-Machine-Learning-Course-master/DecisionTrees &Boosting/.dtree.py.swp 24.6 kB
教程和笔记/Stanford-Machine-Learning-Course-master/DecisionTrees &Boosting/.testdtree.py.swp 20.5 kB
教程和笔记/Stanford-Machine-Learning-Course-master/DecisionTrees &Boosting/breast-cancer-wisconsin.names 5.7 kB
教程和笔记/Stanford-Machine-Learning-Course-master/DecisionTrees &Boosting/build.log 0 Bytes
教程和笔记/Stanford-Machine-Learning-Course-master/DecisionTrees &Boosting/call_graph.png 240.6 kB
教程和笔记/Stanford-Machine-Learning-Course-master/DecisionTrees &Boosting/data.csv 2.1 kB
教程和笔记/Stanford-Machine-Learning-Course-master/DecisionTrees &Boosting/dtree.py 23.2 kB
教程和笔记/Stanford-Machine-Learning-Course-master/DecisionTrees &Boosting/dtree.pyc 27.2 kB
教程和笔记/Stanford-Machine-Learning-Course-master/DecisionTrees &Boosting/dtree1.py 22.4 kB
教程和笔记/Stanford-Machine-Learning-Course-master/DecisionTrees &Boosting/dttasks.py 11.3 kB
教程和笔记/Stanford-Machine-Learning-Course-master/DecisionTrees &Boosting/dttasks.pyc 14.4 kB
教程和笔记/Stanford-Machine-Learning-Course-master/DecisionTrees &Boosting/events.sqlite 264.2 kB
教程和笔记/Stanford-Machine-Learning-Course-master/DecisionTrees &Boosting/hw1.bat 56 Bytes
教程和笔记/Stanford-Machine-Learning-Course-master/DecisionTrees &Boosting/hw1.pdf 284.9 kB
教程和笔记/Stanford-Machine-Learning-Course-master/DecisionTrees &Boosting/Makefile 41 Bytes
教程和笔记/Stanford-Machine-Learning-Course-master/DecisionTrees &Boosting/noisy.dat 2.1 kB
教程和笔记/Stanford-Machine-Learning-Course-master/DecisionTrees &Boosting/submit.sh 563 Bytes
教程和笔记/Stanford-Machine-Learning-Course-master/DecisionTrees &Boosting/testdtree.py 27.4 kB
教程和笔记/Stanford-Machine-Learning-Course-master/DecisionTrees &Boosting/testdtree.pyc 29.3 kB
教程和笔记/Stanford-Machine-Learning-Course-master/DecisionTrees &Boosting/view.txt 4.6 kB
教程和笔记/Stanford-Machine-Learning-Course-master/HMM/.hmm.py.swp 36.9 kB
教程和笔记/Stanford-Machine-Learning-Course-master/HMM/classify.py 3.5 kB
教程和笔记/Stanford-Machine-Learning-Course-master/HMM/classify.pyc 3.4 kB
教程和笔记/Stanford-Machine-Learning-Course-master/HMM/dataset.py 4.3 kB
教程和笔记/Stanford-Machine-Learning-Course-master/HMM/dataset.pyc 4.4 kB
教程和笔记/Stanford-Machine-Learning-Course-master/HMM/events.sqlite 39.9 kB
教程和笔记/Stanford-Machine-Learning-Course-master/HMM/hmm.py 19.6 kB
教程和笔记/Stanford-Machine-Learning-Course-master/HMM/hmm.pyc 18.2 kB
教程和笔记/Stanford-Machine-Learning-Course-master/HMM/hw4.bat 56 Bytes
教程和笔记/Stanford-Machine-Learning-Course-master/HMM/Makefile 41 Bytes
教程和笔记/Stanford-Machine-Learning-Course-master/HMM/robot_no_momentum.data 480.8 kB
教程和笔记/Stanford-Machine-Learning-Course-master/HMM/robot_small.data 159 Bytes
教程和笔记/Stanford-Machine-Learning-Course-master/HMM/robot_with_momentum.data 480.8 kB
教程和笔记/Stanford-Machine-Learning-Course-master/HMM/submit.sh 598 Bytes
教程和笔记/Stanford-Machine-Learning-Course-master/HMM/task_hmm.py 6.9 kB
教程和笔记/Stanford-Machine-Learning-Course-master/HMM/task_hmm.pyc 7.9 kB
教程和笔记/Stanford-Machine-Learning-Course-master/HMM/test_hmm.py 5.0 kB
教程和笔记/Stanford-Machine-Learning-Course-master/HMM/test_hmm.pyc 6.0 kB
教程和笔记/Stanford-Machine-Learning-Course-master/HMM/util.py 1.9 kB
教程和笔记/Stanford-Machine-Learning-Course-master/HMM/util.pyc 2.7 kB
教程和笔记/Stanford-Machine-Learning-Course-master/HMM/viterbi.py 2.3 kB
教程和笔记/Stanford-Machine-Learning-Course-master/HMM/viterbi.pyc 2.7 kB
教程和笔记/Stanford-Machine-Learning-Course-master/HMM/weather_all.data 406.8 kB
教程和笔记/Stanford-Machine-Learning-Course-master/HMM/weather_bos_la.data 202.5 kB
教程和笔记/Stanford-Machine-Learning-Course-master/HMM/weather_bos_sea.data 213.7 kB
教程和笔记/Stanford-Machine-Learning-Course-master/K-Means Clustering and PCA/ex7.pdf 750.3 kB
教程和笔记/Stanford-Machine-Learning-Course-master/K-Means Clustering and PCA/mlclass-ex7/bird_small.mat 45.6 kB
教程和笔记/Stanford-Machine-Learning-Course-master/K-Means Clustering and PCA/mlclass-ex7/bird_small.png 33.0 kB
教程和笔记/Stanford-Machine-Learning-Course-master/K-Means Clustering and PCA/mlclass-ex7/computeCentroids.m 1.3 kB
教程和笔记/Stanford-Machine-Learning-Course-master/K-Means Clustering and PCA/mlclass-ex7/displayData.m 1.5 kB
教程和笔记/Stanford-Machine-Learning-Course-master/K-Means Clustering and PCA/mlclass-ex7/drawLine.m 232 Bytes
教程和笔记/Stanford-Machine-Learning-Course-master/K-Means Clustering and PCA/mlclass-ex7/ex7.m 5.6 kB
教程和笔记/Stanford-Machine-Learning-Course-master/K-Means Clustering and PCA/mlclass-ex7/ex7_pca.m 7.2 kB
教程和笔记/Stanford-Machine-Learning-Course-master/K-Means Clustering and PCA/mlclass-ex7/ex7data1.mat 995 Bytes
教程和笔记/Stanford-Machine-Learning-Course-master/K-Means Clustering and PCA/mlclass-ex7/ex7data2.mat 4.8 kB
教程和笔记/Stanford-Machine-Learning-Course-master/K-Means Clustering and PCA/mlclass-ex7/ex7faces.mat 11.0 MB
教程和笔记/Stanford-Machine-Learning-Course-master/K-Means Clustering and PCA/mlclass-ex7/featureNormalize.m 510 Bytes
教程和笔记/Stanford-Machine-Learning-Course-master/K-Means Clustering and PCA/mlclass-ex7/findClosestCentroids.m 1.1 kB
教程和笔记/Stanford-Machine-Learning-Course-master/K-Means Clustering and PCA/mlclass-ex7/kMeansInitCentroids.m 668 Bytes
教程和笔记/Stanford-Machine-Learning-Course-master/K-Means Clustering and PCA/mlclass-ex7/octave-core 42.6 MB
教程和笔记/Stanford-Machine-Learning-Course-master/K-Means Clustering and PCA/mlclass-ex7/pca.m 900 Bytes
教程和笔记/Stanford-Machine-Learning-Course-master/K-Means Clustering and PCA/mlclass-ex7/plotDataPoints.m 434 Bytes
教程和笔记/Stanford-Machine-Learning-Course-master/K-Means Clustering and PCA/mlclass-ex7/plotProgresskMeans.m 840 Bytes
教程和笔记/Stanford-Machine-Learning-Course-master/K-Means Clustering and PCA/mlclass-ex7/projectData.m 969 Bytes
教程和笔记/Stanford-Machine-Learning-Course-master/K-Means Clustering and PCA/mlclass-ex7/recoverData.m 1.0 kB
教程和笔记/Stanford-Machine-Learning-Course-master/K-Means Clustering and PCA/mlclass-ex7/runkMeans.m 2.0 kB
教程和笔记/Stanford-Machine-Learning-Course-master/K-Means Clustering and PCA/mlclass-ex7/submit.m 8.8 kB
教程和笔记/Stanford-Machine-Learning-Course-master/K-Means Clustering and PCA/mlclass-ex7/submitWeb.m 10.4 kB
教程和笔记/Stanford-Machine-Learning-Course-master/Lectures/aimlcs229/AI-classes.pdf 36.0 kB
教程和笔记/Stanford-Machine-Learning-Course-master/Lectures/aimlcs229/compute_kernel_matrix.txt 222 Bytes
教程和笔记/Stanford-Machine-Learning-Course-master/Lectures/aimlcs229/cs229-cvxopt.pdf 152.4 kB
教程和笔记/Stanford-Machine-Learning-Course-master/Lectures/aimlcs229/cs229-cvxopt2.pdf 201.5 kB
教程和笔记/Stanford-Machine-Learning-Course-master/Lectures/aimlcs229/cs229-gp.pdf 154.6 kB
教程和笔记/Stanford-Machine-Learning-Course-master/Lectures/aimlcs229/cs229-hmm.pdf 202.5 kB
教程和笔记/Stanford-Machine-Learning-Course-master/Lectures/aimlcs229/cs229-linalg.pdf 168.5 kB
教程和笔记/Stanford-Machine-Learning-Course-master/Lectures/aimlcs229/cs229-notes1.pdf 235.2 kB
教程和笔记/Stanford-Machine-Learning-Course-master/Lectures/aimlcs229/cs229-notes10.pdf 77.2 kB
教程和笔记/Stanford-Machine-Learning-Course-master/Lectures/aimlcs229/cs229-notes11.pdf 76.0 kB
教程和笔记/Stanford-Machine-Learning-Course-master/Lectures/aimlcs229/cs229-notes12.pdf 75.7 kB
教程和笔记/Stanford-Machine-Learning-Course-master/Lectures/aimlcs229/cs229-notes2.pdf 878.8 kB
教程和笔记/Stanford-Machine-Learning-Course-master/Lectures/aimlcs229/cs229-notes3.pdf 179.8 kB
教程和笔记/Stanford-Machine-Learning-Course-master/Lectures/aimlcs229/cs229-notes4.pdf 111.3 kB
教程和笔记/Stanford-Machine-Learning-Course-master/Lectures/aimlcs229/cs229-notes5.pdf 88.7 kB
教程和笔记/Stanford-Machine-Learning-Course-master/Lectures/aimlcs229/cs229-notes6.pdf 52.1 kB
教程和笔记/Stanford-Machine-Learning-Course-master/Lectures/aimlcs229/cs229-notes7a.pdf 271.0 kB
教程和笔记/Stanford-Machine-Learning-Course-master/Lectures/aimlcs229/cs229-notes7b.pdf 55.2 kB
教程和笔记/Stanford-Machine-Learning-Course-master/Lectures/aimlcs229/cs229-notes8.pdf 83.1 kB
教程和笔记/Stanford-Machine-Learning-Course-master/Lectures/aimlcs229/cs229-notes9.pdf 83.1 kB
教程和笔记/Stanford-Machine-Learning-Course-master/Lectures/aimlcs229/cs229-prob.pdf 151.0 kB
教程和笔记/Stanford-Machine-Learning-Course-master/Lectures/aimlcs229/emacs.txt 3.7 kB
教程和笔记/Stanford-Machine-Learning-Course-master/Lectures/aimlcs229/gp_demo.txt 5.1 kB
教程和笔记/Stanford-Machine-Learning-Course-master/Lectures/aimlcs229/info.pdf 25.4 kB
教程和笔记/Stanford-Machine-Learning-Course-master/Lectures/aimlcs229/logistic_grad_ascent.txt 576 Bytes
教程和笔记/Stanford-Machine-Learning-Course-master/Lectures/aimlcs229/matlab_el.txt 215.0 kB
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机器学习课程2014源代码/mlclass-ex3-jin/sigmoid.m 137 Bytes
机器学习课程2014源代码/mlclass-ex3-jin/submit.m 17.0 kB
机器学习课程2014源代码/mlclass-ex3-jin/submitWeb.m 807 Bytes
机器学习课程2014源代码/mlclass-ex4-jin/checkNNGradients.m 1.9 kB
机器学习课程2014源代码/mlclass-ex4-jin/computeNumericalGradient.m 1.1 kB
机器学习课程2014源代码/mlclass-ex4-jin/debugInitializeWeights.m 841 Bytes
机器学习课程2014源代码/mlclass-ex4-jin/displayData.m 1.5 kB
机器学习课程2014源代码/mlclass-ex4-jin/ex4.m 8.1 kB
机器学习课程2014源代码/mlclass-ex4-jin/ex4.pdf 416.5 kB
机器学习课程2014源代码/mlclass-ex4-jin/ex4data1.mat 7.5 MB
机器学习课程2014源代码/mlclass-ex4-jin/ex4weights.mat 79.6 kB
机器学习课程2014源代码/mlclass-ex4-jin/fmincg.m 8.7 kB
机器学习课程2014源代码/mlclass-ex4-jin/nnCostFunction.m 5.4 kB
机器学习课程2014源代码/mlclass-ex4-jin/predict.m 585 Bytes
机器学习课程2014源代码/mlclass-ex4-jin/randInitializeWeights.m 980 Bytes
机器学习课程2014源代码/mlclass-ex4-jin/sigmoid.m 137 Bytes
机器学习课程2014源代码/mlclass-ex4-jin/sigmoidGradient.m 712 Bytes
机器学习课程2014源代码/mlclass-ex4-jin/submit.m 17.1 kB
机器学习课程2014源代码/mlclass-ex4-jin/submitWeb.m 807 Bytes
机器学习课程2014源代码/mlclass-ex5-jin/ex5.m 7.4 kB
机器学习课程2014源代码/mlclass-ex5-jin/ex5.pdf 185.9 kB
机器学习课程2014源代码/mlclass-ex5-jin/ex5data1.mat 1.3 kB
机器学习课程2014源代码/mlclass-ex5-jin/featureNormalize.m 510 Bytes
机器学习课程2014源代码/mlclass-ex5-jin/fmincg.m 8.7 kB
机器学习课程2014源代码/mlclass-ex5-jin/learningCurve.m 2.6 kB
机器学习课程2014源代码/mlclass-ex5-jin/linearRegCostFunction.m 1.1 kB
机器学习课程2014源代码/mlclass-ex5-jin/plotFit.m 804 Bytes
机器学习课程2014源代码/mlclass-ex5-jin/polyFeatures.m 709 Bytes
机器学习课程2014源代码/mlclass-ex5-jin/submit.m 17.2 kB
机器学习课程2014源代码/mlclass-ex5-jin/submitWeb.m 807 Bytes
机器学习课程2014源代码/mlclass-ex5-jin/trainLinearReg.m 714 Bytes
机器学习课程2014源代码/mlclass-ex5-jin/validationCurve.m 2.0 kB
机器学习课程2014源代码/mlclass-ex6-jin/dataset3Params.m 2.0 kB
机器学习课程2014源代码/mlclass-ex6-jin/emailFeatures.m 2.1 kB
机器学习课程2014源代码/mlclass-ex6-jin/emailSample1.txt 393 Bytes
机器学习课程2014源代码/mlclass-ex6-jin/emailSample2.txt 1.3 kB
机器学习课程2014源代码/mlclass-ex6-jin/ex6.m 4.1 kB
机器学习课程2014源代码/mlclass-ex6-jin/ex6.pdf 364.0 kB
机器学习课程2014源代码/mlclass-ex6-jin/ex6_spam.m 4.6 kB
机器学习课程2014源代码/mlclass-ex6-jin/ex6data1.mat 981 Bytes
机器学习课程2014源代码/mlclass-ex6-jin/ex6data2.mat 7.6 kB
机器学习课程2014源代码/mlclass-ex6-jin/ex6data3.mat 6.0 kB
机器学习课程2014源代码/mlclass-ex6-jin/gaussianKernel.m 731 Bytes
机器学习课程2014源代码/mlclass-ex6-jin/getVocabList.m 761 Bytes
机器学习课程2014源代码/mlclass-ex6-jin/linearKernel.m 323 Bytes
机器学习课程2014源代码/mlclass-ex6-jin/plotData.m 569 Bytes
机器学习课程2014源代码/mlclass-ex6-jin/porterStemmer.m 9.9 kB
机器学习课程2014源代码/mlclass-ex6-jin/processEmail.m 4.0 kB
机器学习课程2014源代码/mlclass-ex6-jin/readFile.m 396 Bytes
机器学习课程2014源代码/mlclass-ex6-jin/spamSample1.txt 655 Bytes
机器学习课程2014源代码/mlclass-ex6-jin/spamSample2.txt 245 Bytes
机器学习课程2014源代码/mlclass-ex6-jin/spamTest.mat 112.7 kB
机器学习课程2014源代码/mlclass-ex6-jin/spamTrain.mat 428.8 kB
机器学习课程2014源代码/mlclass-ex6-jin/submit.m 16.8 kB
机器学习课程2014源代码/mlclass-ex6-jin/submitWeb.m 807 Bytes
机器学习课程2014源代码/mlclass-ex6-jin/svmPredict.m 1.7 kB
机器学习课程2014源代码/mlclass-ex6-jin/svmTrain.m 6.0 kB
机器学习课程2014源代码/mlclass-ex6-jin/visualizeBoundary.m 734 Bytes
机器学习课程2014源代码/mlclass-ex6-jin/visualizeBoundaryLinear.m 410 Bytes
机器学习课程2014源代码/mlclass-ex6-jin/vocab.txt 20.2 kB
机器学习课程2014源代码/mlclass-ex7-jin/bird_small.mat 45.6 kB
机器学习课程2014源代码/mlclass-ex7-jin/bird_small.png 33.0 kB
机器学习课程2014源代码/mlclass-ex7-jin/computeCentroids.m 1.3 kB
机器学习课程2014源代码/mlclass-ex7-jin/displayData.m 1.5 kB
机器学习课程2014源代码/mlclass-ex7-jin/drawLine.m 232 Bytes
机器学习课程2014源代码/mlclass-ex7-jin/ex7.m 5.6 kB
机器学习课程2014源代码/mlclass-ex7-jin/ex7.pdf 759.9 kB
机器学习课程2014源代码/mlclass-ex7-jin/ex7_pca.m 7.2 kB
机器学习课程2014源代码/mlclass-ex7-jin/ex7data1.mat 995 Bytes
机器学习课程2014源代码/mlclass-ex7-jin/ex7data2.mat 4.8 kB
机器学习课程2014源代码/mlclass-ex7-jin/ex7faces.mat 11.0 MB
机器学习课程2014源代码/mlclass-ex7-jin/featureNormalize.m 510 Bytes
机器学习课程2014源代码/mlclass-ex7-jin/findClosestCentroids.m 1.2 kB
机器学习课程2014源代码/mlclass-ex7-jin/kMeansInitCentroids.m 798 Bytes
机器学习课程2014源代码/mlclass-ex7-jin/pca.m 855 Bytes
机器学习课程2014源代码/mlclass-ex7-jin/plotDataPoints.m 434 Bytes
机器学习课程2014源代码/mlclass-ex7-jin/plotProgresskMeans.m 840 Bytes
机器学习课程2014源代码/mlclass-ex7-jin/projectData.m 953 Bytes
机器学习课程2014源代码/mlclass-ex7-jin/recoverData.m 1.0 kB
机器学习课程2014源代码/mlclass-ex7-jin/runkMeans.m 2.0 kB
机器学习课程2014源代码/mlclass-ex7-jin/submit.m 17.0 kB
机器学习课程2014源代码/mlclass-ex7-jin/submitWeb.m 807 Bytes
机器学习课程2014源代码/mlclass-ex8-jin/checkCostFunction.m 1.6 kB
机器学习课程2014源代码/mlclass-ex8-jin/cofiCostFunc.m 2.2 kB
机器学习课程2014源代码/mlclass-ex8-jin/computeNumericalGradient.m 1.1 kB
机器学习课程2014源代码/mlclass-ex8-jin/estimateGaussian.m 976 Bytes
机器学习课程2014源代码/mlclass-ex8-jin/ex8.m 3.8 kB
机器学习课程2014源代码/mlclass-ex8-jin/ex8.pdf 271.0 kB
机器学习课程2014源代码/mlclass-ex8-jin/ex8_cofi.m 7.1 kB
机器学习课程2014源代码/mlclass-ex8-jin/ex8_movieParams.mat 201.2 kB
机器学习课程2014源代码/mlclass-ex8-jin/ex8_movies.mat 223.4 kB
机器学习课程2014源代码/mlclass-ex8-jin/ex8data1.mat 9.5 kB
机器学习课程2014源代码/mlclass-ex8-jin/ex8data2.mat 93.5 kB
机器学习课程2014源代码/mlclass-ex8-jin/fmincg.m 8.7 kB
机器学习课程2014源代码/mlclass-ex8-jin/loadMovieList.m 651 Bytes
机器学习课程2014源代码/mlclass-ex8-jin/movie_ids.txt 48.4 kB
机器学习课程2014源代码/mlclass-ex8-jin/multivariateGaussian.m 808 Bytes
机器学习课程2014源代码/mlclass-ex8-jin/normalizeRatings.m 479 Bytes
机器学习课程2014源代码/mlclass-ex8-jin/selectThreshold.m 1.5 kB
机器学习课程2014源代码/mlclass-ex8-jin/submit.m 17.5 kB
机器学习课程2014源代码/mlclass-ex8-jin/submitWeb.m 807 Bytes
机器学习课程2014源代码/mlclass-ex8-jin/visualizeFit.m 582 Bytes
机器学习课程2014源代码/README.md 1.5 kB
机器学习课程2014源代码/整合pdf/ex1.pdf 521.5 kB
机器学习课程2014源代码/整合pdf/ex2.pdf 192.8 kB
机器学习课程2014源代码/整合pdf/ex3.pdf 335.6 kB
机器学习课程2014源代码/整合pdf/ex4.pdf 416.5 kB
机器学习课程2014源代码/整合pdf/ex5.pdf 185.9 kB
机器学习课程2014源代码/整合pdf/ex6.pdf 364.0 kB
机器学习课程2014源代码/整合pdf/ex7.pdf 759.9 kB
机器学习课程2014源代码/整合pdf/ex8.pdf 271.0 kB
机器学习课程2014源代码/整合pdf/Programming Exercise(机器学习2014练习).pdf 2.7 MB
机器学习课程2014源代码/整合pdf/源代码打印.pdf 2.6 MB
机器学习课程2014源代码/整合pdf/源代码目录.docx 24.1 kB

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