Обратите внимание, что наш сайт не размещает какие-либо файлы из списка. Вы не можете скачать
эти файлы или скачать torrent-файл.
|
[TGx]Downloaded from torrentgalaxy.to .txt |
585б |
0 |
11б |
001 Intro_en.vtt |
865б |
001 Intro_en.vtt |
5.39Кб |
001 Intro_en.vtt |
3.18Кб |
001 Intro_en.vtt |
473б |
001 Intro_en.vtt |
1.19Кб |
001 Intro.mp4 |
632.60Кб |
001 Intro.mp4 |
10.37Мб |
001 Intro.mp4 |
5.97Мб |
001 Intro.mp4 |
2.89Мб |
001 Intro.mp4 |
2.52Мб |
001 Introduction_en.vtt |
2.22Кб |
001 Introduction_en.vtt |
2.57Кб |
001 Introduction_en.vtt |
1.23Кб |
001 Introduction.mp4 |
41.80Мб |
001 Introduction.mp4 |
25.31Мб |
001 Introduction.mp4 |
2.23Мб |
001 Introduction and Terminology_en.vtt |
8.34Кб |
001 Introduction and Terminology.mp4 |
18.13Мб |
001 Introduction to Transformers_en.vtt |
1.63Кб |
001 Introduction to Transformers.mp4 |
3.41Мб |
001 Kaggle part 1_en.vtt |
2.63Кб |
001 Kaggle part 1.mp4 |
6.75Мб |
001 Principal Component Analysis (PCA) theory_en.vtt |
8.98Кб |
001 Principal Component Analysis (PCA) theory.mp4 |
20.54Мб |
001 Some advice on your journey_en.vtt |
3.78Кб |
001 Some advice on your journey.mp4 |
13.56Мб |
001 Transfer Learning Introduction_en.vtt |
1.99Кб |
001 Transfer Learning Introduction.mp4 |
4.46Мб |
001 Word2vec and Embeddings_en.vtt |
8.33Кб |
001 Word2vec and Embeddings.mp4 |
43.96Мб |
001 Your reviews are important to me!.mp4 |
2.05Мб |
002 Basic Data Structures_en.vtt |
6.41Кб |
002 Basic Data Structures.mp4 |
21.89Мб |
002 Bayesian Learning Distributions_en.vtt |
10.45Кб |
002 Bayesian Learning Distributions.mp4 |
35.95Мб |
002 Coco Dataset + Augmentations for Segmentation with Torchvision_en.vtt |
5.94Кб |
002 Coco Dataset + Augmentations for Segmentation with Torchvision.mp4 |
18.90Мб |
002 DL theory part 1_en.vtt |
6.15Кб |
002 DL theory part 1.mp4 |
17.23Мб |
002 Fashion MNIST feed forward net for benchmarking_en.vtt |
3.50Кб |
002 Fashion MNIST feed forward net for benchmarking.mp4 |
19.66Мб |
002 Fashion MNIST PCA_en.vtt |
10.46Кб |
002 Fashion MNIST PCA.mp4 |
102.09Мб |
002 How to tackle this course_en.vtt |
6.21Кб |
002 How to tackle this course.mp4 |
48.85Мб |
002 Kaggle + Word2Vec_en.vtt |
10.54Кб |
002 Kaggle + Word2Vec.mp4 |
27.79Мб |
002 Kaggle part 2_en.vtt |
3.27Кб |
002 Kaggle part 2.mp4 |
11.13Мб |
002 Kaggle problem description_en.vtt |
2.79Кб |
002 Kaggle problem description.mp4 |
9.19Мб |
002 ----------- Numpy -------------.html |
129б |
002 Pytorch TensorDataset_en.vtt |
5.01Кб |
002 Pytorch TensorDataset.mp4 |
12.40Мб |
002 Saving Models_en.vtt |
3.12Кб |
002 Saving Models.mp4 |
7.56Мб |
002 Stop words and Term Frequency_en.vtt |
4.94Кб |
002 Stop words and Term Frequency.mp4 |
10.70Мб |
002 The illustrated Transformer (blogpost by Jay Alammar)_en.vtt |
8.95Кб |
002 The illustrated Transformer (blogpost by Jay Alammar).mp4 |
23.59Мб |
003 Bayes rule for population mean estimation_en.vtt |
8.98Кб |
003 Bayes rule for population mean estimation.mp4 |
50.16Мб |
003 Dictionaries_en.vtt |
3.80Кб |
003 Dictionaries.mp4 |
18.79Мб |
003 DL theory part 2_en.vtt |
3.94Кб |
003 DL theory part 2.mp4 |
22.80Мб |
003 Encoder Transformer Models The Maths_en.vtt |
5.59Кб |
003 Encoder Transformer Models The Maths.mp4 |
28.66Мб |
003 FastAPI intro_en.vtt |
5.31Кб |
003 FastAPI intro.mp4 |
11.64Мб |
003 Gradient Descent_en.vtt |
16.58Кб |
003 Gradient Descent.mp4 |
43.40Мб |
003 Installations and sign ups_en.vtt |
4.75Кб |
003 Installations and sign ups.mp4 |
42.79Мб |
003 Keras Conv2D layer_en.vtt |
8.57Кб |
003 Keras Conv2D layer.mp4 |
44.46Мб |
003 K-means_en.vtt |
7.61Кб |
003 K-means.mp4 |
22.30Мб |
003 Pytorch Dataset and DataLoaders_en.vtt |
5.73Кб |
003 Pytorch Dataset and DataLoaders.mp4 |
35.35Мб |
003 PyTorch datasets + Torchvision_en.vtt |
4.19Кб |
003 PyTorch datasets + Torchvision.mp4 |
14.72Мб |
003 Term Frequency - Inverse Document Frequency (Tf - Idf) theory_en.vtt |
3.04Кб |
003 Term Frequency - Inverse Document Frequency (Tf - Idf) theory.mp4 |
6.05Мб |
003 Theory part 1_en.vtt |
6.74Кб |
003 Theory part 1.mp4 |
13.54Мб |
003 Unet Architecture overview_en.vtt |
6.37Кб |
003 Unet Architecture overview.mp4 |
14.70Мб |
003 Word2Vec keras Model API_en.vtt |
13.27Кб |
003 Word2Vec keras Model API.mp4 |
45.20Мб |
004 Bayesian learning Population estimation pymc3 way_en.vtt |
8.86Кб |
004 Bayesian learning Population estimation pymc3 way.mp4 |
70.57Мб |
004 BERT - The theory_en.vtt |
3.77Кб |
004 BERT - The theory.mp4 |
8.14Мб |
004 Deep Learning with PyTorch nn.Sequential models_en.vtt |
5.70Кб |
004 Deep Learning with PyTorch nn.Sequential models.mp4 |
11.04Мб |
004 FastAPI serving model_en.vtt |
7.51Кб |
004 FastAPI serving model.mp4 |
29.27Мб |
004 Financial News Sentiment Classifier_en.vtt |
9.99Кб |
004 Financial News Sentiment Classifier.mp4 |
33.71Мб |
004 Jupyter Notebooks_en.vtt |
4.94Кб |
004 Jupyter Notebooks.mp4 |
8.71Мб |
004 Kmeans part 1_en.vtt |
11.79Кб |
004 Kmeans part 1.mp4 |
78.37Мб |
004 Model fitting and discussion of results_en.vtt |
2.91Кб |
004 Model fitting and discussion of results.mp4 |
17.41Мб |
004 Other clustering methods_en.vtt |
7.17Кб |
004 Other clustering methods.mp4 |
48.05Мб |
004 Python functions (methods)_en.vtt |
5.55Кб |
004 Python functions (methods).mp4 |
27.58Мб |
004 PyTorch Model Architecture_en.vtt |
3.58Кб |
004 PyTorch Model Architecture.mp4 |
13.55Мб |
004 PyTorch transfer learning with ResNet_en.vtt |
4.43Кб |
004 PyTorch transfer learning with ResNet.mp4 |
15.43Мб |
004 Recurrent Neural Nets - Theory_en.vtt |
10.55Кб |
004 Recurrent Neural Nets - Theory.mp4 |
19.06Мб |
004 Tensorflow + Keras demo problem 1_en.vtt |
16.43Кб |
004 Tensorflow + Keras demo problem 1.mp4 |
43.33Мб |
004 Theory part 2 + code_en.vtt |
6.28Кб |
004 Theory part 2 + code.mp4 |
27.28Мб |
005 Activation functions_en.vtt |
5.51Кб |
005 Activation functions.mp4 |
15.37Мб |
005 Coin Toss Example with Pymc3_en.vtt |
8.03Кб |
005 Coin Toss Example with Pymc3.mp4 |
70.71Мб |
005 Course Material.html |
130б |
005 DBSCAN theory_en.vtt |
6.90Кб |
005 DBSCAN theory.mp4 |
13.21Мб |
005 Deep Learning - Long Short Term Memory (LSTM) Nets_en.vtt |
11.78Кб |
005 Deep Learning - Long Short Term Memory (LSTM) Nets.mp4 |
90.97Мб |
005 Deep Learning with Pytorch Loss functions_en.vtt |
8.69Кб |
005 Deep Learning with Pytorch Loss functions.mp4 |
52.44Мб |
005 Dropout theory and code_en.vtt |
6.99Кб |
005 Dropout theory and code.mp4 |
23.67Мб |
005 Kaggle Multi-lingual Toxic Comment Classification Challenge_en.vtt |
1.97Кб |
005 Kaggle Multi-lingual Toxic Comment Classification Challenge.mp4 |
6.82Мб |
005 Kmeans part 2_en.vtt |
19.71Кб |
005 Kmeans part 2.mp4 |
63.19Мб |
005 NLTK + Stemming_en.vtt |
7.82Кб |
005 NLTK + Stemming.mp4 |
45.59Мб |
005 Numpy functions_en.vtt |
10.64Кб |
005 Numpy functions.mp4 |
62.44Мб |
005 PyTorch Hooks_en.vtt |
7.29Кб |
005 PyTorch Hooks.mp4 |
24.69Мб |
005 PyTorch Lightning Model_en.vtt |
3.94Кб |
005 PyTorch Lightning Model.mp4 |
9.42Мб |
005 Streamlit Intro_en.vtt |
2.56Кб |
005 Streamlit Intro.mp4 |
5.95Мб |
005 Titanic dataset_en.vtt |
15.21Кб |
005 Titanic dataset.mp4 |
116.30Мб |
006 Broadcasting_en.vtt |
9.64Кб |
006 Broadcasting.mp4 |
27.13Мб |
006 Conditional statements_en.vtt |
3.92Кб |
006 Conditional statements.mp4 |
12.60Мб |
006 Data Setup for Bayesian Linear Regression_en.vtt |
4.71Кб |
006 Data Setup for Bayesian Linear Regression.mp4 |
17.11Мб |
006 Deep Learning - Stacking LSTMs + GRUs_en.vtt |
2.15Кб |
006 Deep Learning - Stacking LSTMs + GRUs.mp4 |
5.03Мб |
006 Deep Learning with Pytorch Stochastic Gradient Descent_en.vtt |
8.07Кб |
006 Deep Learning with Pytorch Stochastic Gradient Descent.mp4 |
79.46Мб |
006 First example with Relu_en.vtt |
5.40Кб |
006 First example with Relu.mp4 |
32.62Мб |
006 Gaussian Mixture Models (GMM) theory_en.vtt |
7.88Кб |
006 Gaussian Mixture Models (GMM) theory.mp4 |
19.99Мб |
006 MaxPool (and comparison to stride)_en.vtt |
5.39Кб |
006 MaxPool (and comparison to stride).mp4 |
17.68Мб |
006 N-grams_en.vtt |
4.04Кб |
006 N-grams.mp4 |
13.79Мб |
006 PyTorch Hooks Step through with breakpoints_en.vtt |
8.80Кб |
006 PyTorch Hooks Step through with breakpoints.mp4 |
67.56Мб |
006 PyTorch Lightning Trainer + Model evaluation_en.vtt |
6.33Кб |
006 PyTorch Lightning Trainer + Model evaluation.mp4 |
50.24Мб |
006 Sklearn classification prelude_en.vtt |
5.26Кб |
006 Sklearn classification prelude.mp4 |
14.31Мб |
006 Streamlit functions_en.vtt |
6.07Кб |
006 Streamlit functions.mp4 |
20.79Мб |
006 Tokenizers and data prep for BERT models_en.vtt |
10.79Кб |
006 Tokenizers and data prep for BERT models.mp4 |
29.06Мб |
007 Bayesian Linear Regression with pymc3_en.vtt |
9.97Кб |
007 Bayesian Linear Regression with pymc3.mp4 |
60.07Мб |
007 Cifar-10_en.vtt |
10.08Кб |
007 Cifar-10.mp4 |
27.28Мб |
007 CLIP model_en.vtt |
7.32Кб |
007 CLIP model.mp4 |
18.74Мб |
007 Deep Learning for Cassava Leaf Classification_en.vtt |
1.07Кб |
007 Deep Learning for Cassava Leaf Classification.mp4 |
4.14Мб |
007 Deep Learning with Pytorch Optimizers_en.vtt |
3.40Кб |
007 Deep Learning with Pytorch Optimizers.mp4 |
10.19Мб |
007 Distilbert (Smaller BERT) model_en.vtt |
10.77Кб |
007 Distilbert (Smaller BERT) model.mp4 |
48.78Мб |
007 For loops_en.vtt |
4.17Кб |
007 For loops.mp4 |
12.38Мб |
007 MNIST and Softmax_en.vtt |
10.43Кб |
007 MNIST and Softmax.mp4 |
55.76Мб |
007 PyTorch Weighted CrossEntropy Loss_en.vtt |
9.06Кб |
007 PyTorch Weighted CrossEntropy Loss.mp4 |
65.19Мб |
007 ---------------- Scikit Learn -------------------------------------.html |
72б |
007 Sklearn classification_en.vtt |
14.46Кб |
007 Sklearn classification.mp4 |
89.99Мб |
007 Transfer Learning - GLOVE vectors_en.vtt |
11.45Кб |
007 Transfer Learning - GLOVE vectors.mp4 |
74.57Мб |
007 Word (feature) importance_en.vtt |
3.75Кб |
007 Word (feature) importance.mp4 |
12.41Мб |
008 Bayesian Rolling Regression - Problem setup_en.vtt |
5.60Кб |
008 Bayesian Rolling Regression - Problem setup.mp4 |
14.84Мб |
008 Cassava Leaf Dataset_en.vtt |
4.85Кб |
008 Cassava Leaf Dataset.mp4 |
15.28Мб |
008 Dealing with missing values_en.vtt |
5.75Кб |
008 Dealing with missing values.mp4 |
50.76Мб |
008 Deep Learning Input Normalisation_en.vtt |
3.16Кб |
008 Deep Learning Input Normalisation.mp4 |
10.35Мб |
008 Dictionaries again_en.vtt |
3.11Кб |
008 Dictionaries again.mp4 |
6.17Мб |
008 Intro_en.vtt |
4.95Кб |
008 Intro.mp4 |
35.38Мб |
008 Nose Tip detection with CNNs_en.vtt |
12.48Кб |
008 Nose Tip detection with CNNs.mp4 |
68.69Мб |
008 Pytorch Lightning + DistilBERT for classification_en.vtt |
17.26Кб |
008 Pytorch Lightning + DistilBERT for classification.mp4 |
102.68Мб |
008 Pytorch Model API_en.vtt |
5.50Кб |
008 Pytorch Model API.mp4 |
33.24Мб |
008 Sequence to Sequence Introduction + Data Prep_en.vtt |
7.99Кб |
008 Sequence to Sequence Introduction + Data Prep.mp4 |
80.10Мб |
008 Spacy intro_en.vtt |
5.58Кб |
008 Spacy intro.mp4 |
33.22Мб |
008 Weights and Biases Logging images_en.vtt |
1.92Кб |
008 Weights and Biases Logging images.mp4 |
15.83Мб |
009 Bayesian Rolling regression - pymc3 way_en.vtt |
9.26Кб |
009 Bayesian Rolling regression - pymc3 way.mp4 |
54.76Мб |
009 Data Augmentation with Torchvision Transforms_en.vtt |
5.90Кб |
009 Data Augmentation with Torchvision Transforms.mp4 |
56.52Мб |
009 Feature Extraction with Spacy (using Pandas)_en.vtt |
9.84Кб |
009 Feature Extraction with Spacy (using Pandas).mp4 |
76.46Мб |
009 Linear Regresson Part 1_en.vtt |
12.25Кб |
009 Linear Regresson Part 1.mp4 |
90.54Мб |
009 -------------------------------- Pandas --------------------------------.html |
61б |
009 Pytorch in GPUs_en.vtt |
2.57Кб |
009 Pytorch in GPUs.mp4 |
4.97Мб |
009 Semantic Segmentation training with PyTorch Lightning_en.vtt |
16.21Кб |
009 Semantic Segmentation training with PyTorch Lightning.mp4 |
130.17Мб |
009 Sequence to Sequence model + Keras Model API_en.vtt |
8.73Кб |
009 Sequence to Sequence model + Keras Model API.mp4 |
30.48Мб |
009 Softmax theory_en.vtt |
5.52Кб |
009 Softmax theory.mp4 |
58.32Мб |
009 --------- Time Series -------------------.html |
255б |
010 Batch Norm_en.vtt |
5.66Кб |
010 Batch Norm.mp4 |
17.04Мб |
010 Bayesian Rolling Regression - forecasting_en.vtt |
5.34Кб |
010 Bayesian Rolling Regression - forecasting.mp4 |
30.34Мб |
010 Classification Example_en.vtt |
4.28Кб |
010 Classification Example.mp4 |
24.10Мб |
010 Deep Learning Intro to Pytorch Lightning_en.vtt |
9.27Кб |
010 Deep Learning Intro to Pytorch Lightning.mp4 |
52.37Мб |
010 Intro_en.vtt |
2.41Кб |
010 Intro_en.vtt |
5.91Кб |
010 Intro.mp4 |
11.41Мб |
010 Intro.mp4 |
5.02Мб |
010 Linear Regression Part 2_en.vtt |
11.21Кб |
010 Linear Regression Part 2.mp4 |
71.55Мб |
010 Sequence to Sequence models Prediction step_en.vtt |
13.13Кб |
010 Sequence to Sequence models Prediction step.mp4 |
104.69Мб |
010 Train vs Test Augmentations + DataLoader parameters_en.vtt |
3.31Кб |
010 Train vs Test Augmentations + DataLoader parameters.mp4 |
7.73Мб |
011 Batch Norm Theory_en.vtt |
8.29Кб |
011 Batch Norm Theory.mp4 |
53.89Мб |
011 Classification and Regression Trees_en.vtt |
6.44Кб |
011 Classification and Regression Trees.mp4 |
19.98Мб |
011 Deep Learning Transfer Learning Model with ResNet_en.vtt |
3.30Кб |
011 Deep Learning Transfer Learning Model with ResNet.mp4 |
8.01Мб |
011 Loss functions_en.vtt |
7.15Кб |
011 Loss functions.mp4 |
46.45Мб |
011 Over-sampling_en.vtt |
5.81Кб |
011 Over-sampling.mp4 |
32.84Мб |
011 Pandas simple functions_en.vtt |
11.39Кб |
011 Pandas simple functions.mp4 |
38.33Мб |
011 Variational Bayes Intro_en.vtt |
3.22Кб |
011 Variational Bayes Intro.mp4 |
8.64Мб |
012 CART part 2_en.vtt |
20.53Кб |
012 CART part 2.mp4 |
166.49Мб |
012 FB Prophet part 1_en.vtt |
9.77Кб |
012 FB Prophet part 1.mp4 |
78.03Мб |
012 Pandas Subsetting_en.vtt |
6.27Кб |
012 Pandas Subsetting.mp4 |
22.05Мб |
012 -------- Regularization ------------.html |
218б |
012 Setting up PyTorch Lightning for training_en.vtt |
3.53Кб |
012 Setting up PyTorch Lightning for training.mp4 |
8.36Мб |
012 Variational Bayes Linear Classification_en.vtt |
7.51Кб |
012 Variational Bayes Linear Classification.mp4 |
44.30Мб |
013 Cross Entropy Loss for Imbalanced Classes_en.vtt |
3.95Кб |
013 Cross Entropy Loss for Imbalanced Classes.mp4 |
8.50Мб |
013 FB Prophet part 2_en.vtt |
4.09Кб |
013 FB Prophet part 2.mp4 |
24.45Мб |
013 Introduction_en.vtt |
2.62Кб |
013 Introduction.mp4 |
8.35Мб |
013 Pandas loc and iloc_en.vtt |
7.62Кб |
013 Pandas loc and iloc.mp4 |
41.82Мб |
013 Random Forest theory_en.vtt |
2.53Кб |
013 Random Forest theory.mp4 |
4.82Мб |
013 Variational Bayesian Inference Result Analysis_en.vtt |
3.75Кб |
013 Variational Bayesian Inference Result Analysis.mp4 |
7.37Мб |
014 Minibatch Variational Bayes_en.vtt |
3.86Кб |
014 Minibatch Variational Bayes.mp4 |
11.05Мб |
014 MSE recap_en.vtt |
6.14Кб |
014 MSE recap.mp4 |
18.30Мб |
014 Pandas loc and iloc 2_en.vtt |
5.21Кб |
014 Pandas loc and iloc 2.mp4 |
13.84Мб |
014 PyTorch Test dataset setup and evaluation_en.vtt |
2.87Кб |
014 PyTorch Test dataset setup and evaluation.mp4 |
7.10Мб |
014 Random Forest Code_en.vtt |
6.66Кб |
014 Random Forest Code.mp4 |
36.74Мб |
014 Theory behind FB Prophet_en.vtt |
5.89Кб |
014 Theory behind FB Prophet.mp4 |
16.86Мб |
015 Deep Bayesian Networks_en.vtt |
3.17Кб |
015 Deep Bayesian Networks.mp4 |
7.27Мб |
015 Gradient Boosted Machines_en.vtt |
9.70Кб |
015 Gradient Boosted Machines.mp4 |
67.61Мб |
015 L2 Loss Ridge Regression intro_en.vtt |
3.57Кб |
015 L2 Loss Ridge Regression intro.mp4 |
10.04Мб |
015 ------------ Model Diagnostics -----.html |
112б |
015 Pandas map and apply_en.vtt |
8.21Кб |
015 Pandas map and apply.mp4 |
31.43Мб |
015 WandB for logging experiments_en.vtt |
5.39Кб |
015 WandB for logging experiments.mp4 |
21.51Мб |
016 Deep Bayesian Networks - analysis_en.vtt |
4.07Кб |
016 Deep Bayesian Networks - analysis.mp4 |
10.49Мб |
016 Overfitting_en.vtt |
6.99Кб |
016 Overfitting.mp4 |
19.33Мб |
016 Pandas groupby_en.vtt |
7.04Кб |
016 Pandas groupby.mp4 |
18.34Мб |
016 Ridge regression (L2 penalised regression)_en.vtt |
7.90Кб |
016 Ridge regression (L2 penalised regression).mp4 |
46.97Мб |
017 Cross Validation_en.vtt |
8.26Кб |
017 Cross Validation.mp4 |
53.72Мб |
017 ----- Plotting --------.html |
47б |
017 S&P500 data preparation for L1 loss_en.vtt |
7.13Кб |
017 S&P500 data preparation for L1 loss.mp4 |
25.22Мб |
018 L1 Penalised Regression (Lasso)_en.vtt |
5.60Кб |
018 L1 Penalised Regression (Lasso).mp4 |
31.42Мб |
018 Plotting resources (notebooks).html |
92б |
018 Stratified K Fold_en.vtt |
9.92Кб |
018 Stratified K Fold.mp4 |
58.11Мб |
019 Area Under Curve (AUC) Part 1_en.vtt |
9.21Кб |
019 Area Under Curve (AUC) Part 1.mp4 |
84.11Мб |
019 L1 L2 Penalty theory why it works_en.vtt |
3.78Кб |
019 L1 L2 Penalty theory why it works.mp4 |
23.22Мб |
019 Line plot_en.vtt |
3.24Кб |
019 Line plot.mp4 |
8.55Мб |
020 Area Under Curve (AUC) Part 2_en.vtt |
6.96Кб |
020 Area Under Curve (AUC) Part 2.mp4 |
19.50Мб |
020 Plot multiple lines_en.vtt |
3.91Кб |
020 Plot multiple lines.mp4 |
45.39Мб |
021 Histograms_en.vtt |
7.87Кб |
021 Histograms.mp4 |
21.62Мб |
022 Scatter Plots_en.vtt |
6.39Кб |
022 Scatter Plots.mp4 |
18.60Мб |
023 Subplots_en.vtt |
6.00Кб |
023 Subplots.mp4 |
15.31Мб |
024 Seaborn + pair plots_en.vtt |
7.95Кб |
024 Seaborn + pair plots.mp4 |
49.67Мб |
1 |
399.53Кб |
10 |
920.33Кб |
100 |
103.03Кб |
101 |
213.39Кб |
102 |
262.24Кб |
103 |
409.52Кб |
104 |
672.95Кб |
105 |
716.40Кб |
106 |
885.99Кб |
107 |
322.59Кб |
108 |
607.55Кб |
109 |
791.00Кб |
11 |
552.45Кб |
110 |
906.26Кб |
111 |
979.25Кб |
112 |
148.17Кб |
113 |
169.37Кб |
114 |
584.75Кб |
115 |
643.52Кб |
116 |
705.82Кб |
117 |
732.25Кб |
118 |
159.72Кб |
119 |
282.50Кб |
12 |
647.63Кб |
120 |
303.86Кб |
121 |
708.02Кб |
122 |
159.00Кб |
123 |
215.42Кб |
124 |
447.88Кб |
125 |
463.59Кб |
126 |
475.13Кб |
127 |
808.22Кб |
128 |
410.11Кб |
129 |
603.83Кб |
13 |
997.83Кб |
130 |
618.44Кб |
131 |
635.39Кб |
132 |
367.14Кб |
133 |
600.70Кб |
134 |
885.78Кб |
135 |
977.35Кб |
136 |
978.02Кб |
137 |
310.11Кб |
138 |
527.23Кб |
139 |
648.43Кб |
14 |
557.27Кб |
140 |
666.78Кб |
141 |
833.33Кб |
142 |
983.93Кб |
143 |
598.97Кб |
144 |
833.61Кб |
145 |
294.30Кб |
146 |
366.98Кб |
147 |
456.17Кб |
148 |
516.05Кб |
149 |
656.16Кб |
15 |
436.91Кб |
150 |
660.99Кб |
151 |
877.77Кб |
152 |
1012.18Кб |
153 |
274.64Кб |
154 |
454.03Кб |
155 |
649.71Кб |
156 |
745.80Кб |
157 |
924.43Кб |
158 |
188.20Кб |
159 |
260.44Кб |
16 |
458.36Кб |
160 |
854.11Кб |
161 |
967.74Кб |
162 |
34.75Кб |
163 |
47.32Кб |
164 |
995.88Кб |
165 |
1004.83Кб |
166 |
25.94Кб |
167 |
181.34Кб |
168 |
557.53Кб |
169 |
878.78Кб |
17 |
293.11Кб |
170 |
599.62Кб |
171 |
110.48Кб |
172 |
201.81Кб |
173 |
347.26Кб |
174 |
446.86Кб |
175 |
487.11Кб |
176 |
793.58Кб |
177 |
975.79Кб |
18 |
443.69Кб |
19 |
321.49Кб |
2 |
715.91Кб |
20 |
394.47Кб |
21 |
452.43Кб |
22 |
830.32Кб |
23 |
832.06Кб |
24 |
569.55Кб |
25 |
950.76Кб |
26 |
698.83Кб |
27 |
911.89Кб |
28 |
490.75Кб |
29 |
247.72Кб |
3 |
321.84Кб |
30 |
247.93Кб |
30889860-course-code-material.zip |
26.20Мб |
31 |
111.43Кб |
31237618-03-0-plotting.zip |
2.80Мб |
31283222-multi-plot.py |
440б |
31762302-06-0-reguralisation.zip |
2.56Мб |
31919076-bayesian-inference.zip |
1.80Мб |
32 |
290.45Кб |
32725408-09-tensorflow.zip |
2.66Мб |
33 |
568.43Кб |
34 |
642.33Кб |
34142844-04-pairplots.ipynb |
200.49Кб |
35 |
243.18Кб |
36 |
781.04Кб |
37 |
860.78Кб |
38 |
340.38Кб |
39 |
149.78Кб |
4 |
322.61Кб |
40 |
222.89Кб |
41 |
969.72Кб |
42 |
31.49Кб |
43 |
564.53Кб |
44 |
415.66Кб |
45 |
623.37Кб |
46 |
821.24Кб |
47 |
552.46Кб |
48 |
721.15Кб |
49 |
40.73Кб |
5 |
927.41Кб |
50 |
612.74Кб |
51 |
683.94Кб |
52 |
219.83Кб |
53 |
188.67Кб |
54 |
207.72Кб |
55 |
687.37Кб |
56 |
266.86Кб |
57 |
56.10Кб |
58 |
632.92Кб |
59 |
660.57Кб |
6 |
34.63Кб |
60 |
299.24Кб |
61 |
776.81Кб |
62 |
795.05Кб |
63 |
165.82Кб |
64 |
393.15Кб |
65 |
580.03Кб |
66 |
590.45Кб |
67 |
536.85Кб |
68 |
672.86Кб |
69 |
746.10Кб |
7 |
469.00Кб |
70 |
965.84Кб |
71 |
345.93Кб |
72 |
216.73Кб |
73 |
425.06Кб |
74 |
739.76Кб |
75 |
742.29Кб |
76 |
888.40Кб |
77 |
818.14Кб |
78 |
710.41Кб |
79 |
801.70Кб |
8 |
13.80Кб |
80 |
317.54Кб |
81 |
563.17Кб |
82 |
920.03Кб |
83 |
336.65Кб |
84 |
420.94Кб |
85 |
801.64Кб |
86 |
209.33Кб |
87 |
713.25Кб |
88 |
974.38Кб |
89 |
114.25Кб |
9 |
912.87Кб |
90 |
392.02Кб |
91 |
496.92Кб |
92 |
213.68Кб |
93 |
475.62Кб |
94 |
6.95Кб |
95 |
18.82Кб |
96 |
351.84Кб |
97 |
517.10Кб |
98 |
687.21Кб |
99 |
964.00Кб |
external-assets-links.txt |
264б |
external-assets-links.txt |
122б |
external-assets-links.txt |
52б |
TutsNode.com.txt |
63б |