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| [Tutorialsplanet.NET].url |
128B |
| [Tutorialsplanet.NET].url |
128B |
| [Tutorialsplanet.NET].url |
128B |
| [Tutorialsplanet.NET].url |
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| [Tutorialsplanet.NET].url |
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| 001 Intro_en.vtt |
865B |
| 001 Intro_en.vtt |
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| 001 Intro_en.vtt |
473B |
| 001 Intro_en.vtt |
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| 001 Intro_en.vtt |
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| 001 Intro.mp4 |
2.89MB |
| 001 Intro.mp4 |
10.37MB |
| 001 Intro.mp4 |
632.60KB |
| 001 Intro.mp4 |
5.97MB |
| 001 Intro.mp4 |
2.52MB |
| 001 Introduction_en.vtt |
2.22KB |
| 001 Introduction_en.vtt |
1.23KB |
| 001 Introduction_en.vtt |
2.57KB |
| 001 Introduction.mp4 |
41.80MB |
| 001 Introduction.mp4 |
2.23MB |
| 001 Introduction.mp4 |
25.31MB |
| 001 Introduction and Terminology_en.vtt |
8.34KB |
| 001 Introduction and Terminology.mp4 |
18.13MB |
| 001 Introduction to Transformers_en.vtt |
1.63KB |
| 001 Introduction to Transformers.mp4 |
3.41MB |
| 001 Kaggle part 1_en.vtt |
2.63KB |
| 001 Kaggle part 1.mp4 |
6.75MB |
| 001 Principal Component Analysis (PCA) theory_en.vtt |
8.98KB |
| 001 Principal Component Analysis (PCA) theory.mp4 |
20.54MB |
| 001 Some advice on your journey_en.vtt |
3.78KB |
| 001 Some advice on your journey.mp4 |
13.56MB |
| 001 Transfer Learning Introduction_en.vtt |
1.99KB |
| 001 Transfer Learning Introduction.mp4 |
4.46MB |
| 001 Word2vec and Embeddings_en.vtt |
8.33KB |
| 001 Word2vec and Embeddings.mp4 |
43.96MB |
| 001 Your reviews are important to me!.mp4 |
2.05MB |
| 002 Basic Data Structures_en.vtt |
6.41KB |
| 002 Basic Data Structures.mp4 |
21.89MB |
| 002 Bayesian Learning Distributions_en.vtt |
10.45KB |
| 002 Bayesian Learning Distributions.mp4 |
35.95MB |
| 002 Coco Dataset + Augmentations for Segmentation with Torchvision_en.vtt |
5.94KB |
| 002 Coco Dataset + Augmentations for Segmentation with Torchvision.mp4 |
18.90MB |
| 002 DL theory part 1_en.vtt |
6.15KB |
| 002 DL theory part 1.mp4 |
17.23MB |
| 002 Fashion MNIST feed forward net for benchmarking_en.vtt |
3.50KB |
| 002 Fashion MNIST feed forward net for benchmarking.mp4 |
19.66MB |
| 002 Fashion MNIST PCA_en.vtt |
10.46KB |
| 002 Fashion MNIST PCA.mp4 |
102.09MB |
| 002 How to tackle this course_en.vtt |
6.21KB |
| 002 How to tackle this course.mp4 |
48.85MB |
| 002 Kaggle + Word2Vec_en.vtt |
10.54KB |
| 002 Kaggle + Word2Vec.mp4 |
27.79MB |
| 002 Kaggle part 2_en.vtt |
3.27KB |
| 002 Kaggle part 2.mp4 |
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| 002 Kaggle problem description_en.vtt |
2.79KB |
| 002 Kaggle problem description.mp4 |
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| 002 ----------- Numpy -------------.html |
129B |
| 002 Pytorch TensorDataset_en.vtt |
5.01KB |
| 002 Pytorch TensorDataset.mp4 |
12.40MB |
| 002 Saving Models_en.vtt |
3.12KB |
| 002 Saving Models.mp4 |
7.56MB |
| 002 Stop words and Term Frequency_en.vtt |
4.94KB |
| 002 Stop words and Term Frequency.mp4 |
10.70MB |
| 002 The illustrated Transformer (blogpost by Jay Alammar)_en.vtt |
8.95KB |
| 002 The illustrated Transformer (blogpost by Jay Alammar).mp4 |
23.59MB |
| 003 Bayes rule for population mean estimation_en.vtt |
8.98KB |
| 003 Bayes rule for population mean estimation.mp4 |
50.16MB |
| 003 Dictionaries_en.vtt |
3.80KB |
| 003 Dictionaries.mp4 |
18.79MB |
| 003 DL theory part 2_en.vtt |
3.94KB |
| 003 DL theory part 2.mp4 |
22.80MB |
| 003 Encoder Transformer Models The Maths_en.vtt |
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| 003 Encoder Transformer Models The Maths.mp4 |
28.66MB |
| 003 FastAPI intro_en.vtt |
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| 003 FastAPI intro.mp4 |
11.64MB |
| 003 Gradient Descent_en.vtt |
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| 003 Gradient Descent.mp4 |
43.40MB |
| 003 Installations and sign ups_en.vtt |
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| 003 Installations and sign ups.mp4 |
42.79MB |
| 003 Keras Conv2D layer_en.vtt |
8.57KB |
| 003 Keras Conv2D layer.mp4 |
44.46MB |
| 003 K-means_en.vtt |
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| 003 K-means.mp4 |
22.30MB |
| 003 Pytorch Dataset and DataLoaders_en.vtt |
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| 003 Pytorch Dataset and DataLoaders.mp4 |
35.35MB |
| 003 PyTorch datasets + Torchvision_en.vtt |
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| 003 PyTorch datasets + Torchvision.mp4 |
14.72MB |
| 003 Term Frequency - Inverse Document Frequency (Tf - Idf) theory_en.vtt |
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| 003 Term Frequency - Inverse Document Frequency (Tf - Idf) theory.mp4 |
6.05MB |
| 003 Theory part 1_en.vtt |
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| 003 Theory part 1.mp4 |
13.54MB |
| 003 Unet Architecture overview_en.vtt |
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| 003 Unet Architecture overview.mp4 |
14.70MB |
| 003 Word2Vec keras Model API_en.vtt |
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| 003 Word2Vec keras Model API.mp4 |
45.20MB |
| 004 Bayesian learning Population estimation pymc3 way_en.vtt |
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| 004 Bayesian learning Population estimation pymc3 way.mp4 |
70.57MB |
| 004 BERT - The theory_en.vtt |
3.77KB |
| 004 BERT - The theory.mp4 |
8.14MB |
| 004 Deep Learning with PyTorch nn.Sequential models_en.vtt |
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| 004 Deep Learning with PyTorch nn.Sequential models.mp4 |
11.04MB |
| 004 FastAPI serving model_en.vtt |
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| 004 FastAPI serving model.mp4 |
29.27MB |
| 004 Financial News Sentiment Classifier_en.vtt |
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| 004 Financial News Sentiment Classifier.mp4 |
33.71MB |
| 004 Jupyter Notebooks_en.vtt |
4.94KB |
| 004 Jupyter Notebooks.mp4 |
8.71MB |
| 004 Kmeans part 1_en.vtt |
11.79KB |
| 004 Kmeans part 1.mp4 |
78.37MB |
| 004 Model fitting and discussion of results_en.vtt |
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| 004 Model fitting and discussion of results.mp4 |
17.41MB |
| 004 Other clustering methods_en.vtt |
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| 004 Other clustering methods.mp4 |
48.05MB |
| 004 Python functions (methods)_en.vtt |
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| 004 Python functions (methods).mp4 |
27.58MB |
| 004 PyTorch Model Architecture_en.vtt |
3.58KB |
| 004 PyTorch Model Architecture.mp4 |
13.55MB |
| 004 PyTorch transfer learning with ResNet_en.vtt |
4.43KB |
| 004 PyTorch transfer learning with ResNet.mp4 |
15.43MB |
| 004 Recurrent Neural Nets - Theory_en.vtt |
10.55KB |
| 004 Recurrent Neural Nets - Theory.mp4 |
19.06MB |
| 004 Tensorflow + Keras demo problem 1_en.vtt |
16.43KB |
| 004 Tensorflow + Keras demo problem 1.mp4 |
43.33MB |
| 004 Theory part 2 + code_en.vtt |
6.28KB |
| 004 Theory part 2 + code.mp4 |
27.28MB |
| 005 Activation functions_en.vtt |
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| 005 Activation functions.mp4 |
15.37MB |
| 005 Coin Toss Example with Pymc3_en.vtt |
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| 005 Coin Toss Example with Pymc3.mp4 |
70.71MB |
| 005 Course Material.html |
130B |
| 005 DBSCAN theory_en.vtt |
6.90KB |
| 005 DBSCAN theory.mp4 |
13.21MB |
| 005 Deep Learning - Long Short Term Memory (LSTM) Nets_en.vtt |
11.78KB |
| 005 Deep Learning - Long Short Term Memory (LSTM) Nets.mp4 |
90.97MB |
| 005 Deep Learning with Pytorch Loss functions_en.vtt |
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| 005 Deep Learning with Pytorch Loss functions.mp4 |
52.44MB |
| 005 Dropout theory and code_en.vtt |
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| 005 Dropout theory and code.mp4 |
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| 005 Kaggle Multi-lingual Toxic Comment Classification Challenge_en.vtt |
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| 005 Kaggle Multi-lingual Toxic Comment Classification Challenge.mp4 |
6.82MB |
| 005 Kmeans part 2_en.vtt |
19.71KB |
| 005 Kmeans part 2.mp4 |
63.19MB |
| 005 NLTK + Stemming_en.vtt |
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| 005 NLTK + Stemming.mp4 |
45.59MB |
| 005 Numpy functions_en.vtt |
10.64KB |
| 005 Numpy functions.mp4 |
62.44MB |
| 005 PyTorch Hooks_en.vtt |
7.29KB |
| 005 PyTorch Hooks.mp4 |
24.69MB |
| 005 PyTorch Lightning Model_en.vtt |
3.94KB |
| 005 PyTorch Lightning Model.mp4 |
9.42MB |
| 005 Streamlit Intro_en.vtt |
2.56KB |
| 005 Streamlit Intro.mp4 |
5.95MB |
| 005 Titanic dataset_en.vtt |
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| 005 Titanic dataset.mp4 |
116.30MB |
| 006 Broadcasting_en.vtt |
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| 006 Broadcasting.mp4 |
27.13MB |
| 006 Conditional statements_en.vtt |
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| 006 Conditional statements.mp4 |
12.60MB |
| 006 Data Setup for Bayesian Linear Regression_en.vtt |
4.71KB |
| 006 Data Setup for Bayesian Linear Regression.mp4 |
17.11MB |
| 006 Deep Learning - Stacking LSTMs + GRUs_en.vtt |
2.15KB |
| 006 Deep Learning - Stacking LSTMs + GRUs.mp4 |
5.03MB |
| 006 Deep Learning with Pytorch Stochastic Gradient Descent_en.vtt |
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| 006 Deep Learning with Pytorch Stochastic Gradient Descent.mp4 |
79.46MB |
| 006 First example with Relu_en.vtt |
5.40KB |
| 006 First example with Relu.mp4 |
32.62MB |
| 006 Gaussian Mixture Models (GMM) theory_en.vtt |
7.88KB |
| 006 Gaussian Mixture Models (GMM) theory.mp4 |
19.99MB |
| 006 MaxPool (and comparison to stride)_en.vtt |
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| 006 MaxPool (and comparison to stride).mp4 |
17.68MB |
| 006 N-grams_en.vtt |
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| 006 N-grams.mp4 |
13.79MB |
| 006 PyTorch Hooks Step through with breakpoints_en.vtt |
8.80KB |
| 006 PyTorch Hooks Step through with breakpoints.mp4 |
67.56MB |
| 006 PyTorch Lightning Trainer + Model evaluation_en.vtt |
6.33KB |
| 006 PyTorch Lightning Trainer + Model evaluation.mp4 |
50.24MB |
| 006 Sklearn classification prelude_en.vtt |
5.26KB |
| 006 Sklearn classification prelude.mp4 |
14.31MB |
| 006 Streamlit functions_en.vtt |
6.07KB |
| 006 Streamlit functions.mp4 |
20.79MB |
| 006 Tokenizers and data prep for BERT models_en.vtt |
10.79KB |
| 006 Tokenizers and data prep for BERT models.mp4 |
29.06MB |
| 007 Bayesian Linear Regression with pymc3_en.vtt |
9.97KB |
| 007 Bayesian Linear Regression with pymc3.mp4 |
60.07MB |
| 007 Cifar-10_en.vtt |
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| 007 Cifar-10.mp4 |
27.28MB |
| 007 CLIP model_en.vtt |
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| 007 CLIP model.mp4 |
18.74MB |
| 007 Deep Learning for Cassava Leaf Classification_en.vtt |
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| 007 Deep Learning for Cassava Leaf Classification.mp4 |
4.14MB |
| 007 Deep Learning with Pytorch Optimizers_en.vtt |
3.40KB |
| 007 Deep Learning with Pytorch Optimizers.mp4 |
10.19MB |
| 007 Distilbert (Smaller BERT) model_en.vtt |
10.77KB |
| 007 Distilbert (Smaller BERT) model.mp4 |
48.78MB |
| 007 For loops_en.vtt |
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| 007 For loops.mp4 |
12.38MB |
| 007 MNIST and Softmax_en.vtt |
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| 007 MNIST and Softmax.mp4 |
55.76MB |
| 007 PyTorch Weighted CrossEntropy Loss_en.vtt |
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| 007 PyTorch Weighted CrossEntropy Loss.mp4 |
65.19MB |
| 007 ---------------- Scikit Learn -------------------------------------.html |
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| 007 Sklearn classification_en.vtt |
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| 007 Sklearn classification.mp4 |
89.99MB |
| 007 Transfer Learning - GLOVE vectors_en.vtt |
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| 007 Transfer Learning - GLOVE vectors.mp4 |
74.57MB |
| 007 Word (feature) importance_en.vtt |
3.75KB |
| 007 Word (feature) importance.mp4 |
12.41MB |
| 008 Bayesian Rolling Regression - Problem setup_en.vtt |
5.60KB |
| 008 Bayesian Rolling Regression - Problem setup.mp4 |
14.84MB |
| 008 Cassava Leaf Dataset_en.vtt |
4.85KB |
| 008 Cassava Leaf Dataset.mp4 |
15.28MB |
| 008 Dealing with missing values_en.vtt |
5.75KB |
| 008 Dealing with missing values.mp4 |
50.76MB |
| 008 Deep Learning Input Normalisation_en.vtt |
3.16KB |
| 008 Deep Learning Input Normalisation.mp4 |
10.35MB |
| 008 Dictionaries again_en.vtt |
3.11KB |
| 008 Dictionaries again.mp4 |
6.17MB |
| 008 Intro_en.vtt |
4.95KB |
| 008 Intro.mp4 |
35.38MB |
| 008 Nose Tip detection with CNNs_en.vtt |
12.48KB |
| 008 Nose Tip detection with CNNs.mp4 |
68.69MB |
| 008 Pytorch Lightning + DistilBERT for classification_en.vtt |
17.26KB |
| 008 Pytorch Lightning + DistilBERT for classification.mp4 |
102.68MB |
| 008 Pytorch Model API_en.vtt |
5.50KB |
| 008 Pytorch Model API.mp4 |
33.24MB |
| 008 Sequence to Sequence Introduction + Data Prep_en.vtt |
7.99KB |
| 008 Sequence to Sequence Introduction + Data Prep.mp4 |
80.10MB |
| 008 Spacy intro_en.vtt |
5.58KB |
| 008 Spacy intro.mp4 |
33.22MB |
| 008 Weights and Biases Logging images_en.vtt |
1.92KB |
| 008 Weights and Biases Logging images.mp4 |
15.83MB |
| 009 Bayesian Rolling regression - pymc3 way_en.vtt |
9.26KB |
| 009 Bayesian Rolling regression - pymc3 way.mp4 |
54.76MB |
| 009 Data Augmentation with Torchvision Transforms_en.vtt |
5.90KB |
| 009 Data Augmentation with Torchvision Transforms.mp4 |
56.52MB |
| 009 Feature Extraction with Spacy (using Pandas)_en.vtt |
9.84KB |
| 009 Feature Extraction with Spacy (using Pandas).mp4 |
76.46MB |
| 009 Linear Regresson Part 1_en.vtt |
12.25KB |
| 009 Linear Regresson Part 1.mp4 |
90.54MB |
| 009 -------------------------------- Pandas --------------------------------.html |
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| 009 Pytorch in GPUs_en.vtt |
2.57KB |
| 009 Pytorch in GPUs.mp4 |
4.97MB |
| 009 Semantic Segmentation training with PyTorch Lightning_en.vtt |
16.21KB |
| 009 Semantic Segmentation training with PyTorch Lightning.mp4 |
130.17MB |
| 009 Sequence to Sequence model + Keras Model API_en.vtt |
8.73KB |
| 009 Sequence to Sequence model + Keras Model API.mp4 |
30.48MB |
| 009 Softmax theory_en.vtt |
5.52KB |
| 009 Softmax theory.mp4 |
58.32MB |
| 009 --------- Time Series -------------------.html |
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| 010 Batch Norm_en.vtt |
5.66KB |
| 010 Batch Norm.mp4 |
17.04MB |
| 010 Bayesian Rolling Regression - forecasting_en.vtt |
5.34KB |
| 010 Bayesian Rolling Regression - forecasting.mp4 |
30.34MB |
| 010 Classification Example_en.vtt |
4.28KB |
| 010 Classification Example.mp4 |
24.10MB |
| 010 Deep Learning Intro to Pytorch Lightning_en.vtt |
9.27KB |
| 010 Deep Learning Intro to Pytorch Lightning.mp4 |
52.37MB |
| 010 Intro_en.vtt |
2.41KB |
| 010 Intro_en.vtt |
5.91KB |
| 010 Intro.mp4 |
5.02MB |
| 010 Intro.mp4 |
11.41MB |
| 010 Linear Regression Part 2_en.vtt |
11.21KB |
| 010 Linear Regression Part 2.mp4 |
71.55MB |
| 010 Sequence to Sequence models Prediction step_en.vtt |
13.13KB |
| 010 Sequence to Sequence models Prediction step.mp4 |
104.69MB |
| 010 Train vs Test Augmentations + DataLoader parameters_en.vtt |
3.31KB |
| 010 Train vs Test Augmentations + DataLoader parameters.mp4 |
7.73MB |
| 011 Batch Norm Theory_en.vtt |
8.29KB |
| 011 Batch Norm Theory.mp4 |
53.89MB |
| 011 Classification and Regression Trees_en.vtt |
6.44KB |
| 011 Classification and Regression Trees.mp4 |
19.98MB |
| 011 Deep Learning Transfer Learning Model with ResNet_en.vtt |
3.30KB |
| 011 Deep Learning Transfer Learning Model with ResNet.mp4 |
8.01MB |
| 011 Loss functions_en.vtt |
7.15KB |
| 011 Loss functions.mp4 |
46.45MB |
| 011 Over-sampling_en.vtt |
5.81KB |
| 011 Over-sampling.mp4 |
32.84MB |
| 011 Pandas simple functions_en.vtt |
11.39KB |
| 011 Pandas simple functions.mp4 |
38.33MB |
| 011 Variational Bayes Intro_en.vtt |
3.22KB |
| 011 Variational Bayes Intro.mp4 |
8.64MB |
| 012 CART part 2_en.vtt |
20.53KB |
| 012 CART part 2.mp4 |
166.49MB |
| 012 FB Prophet part 1_en.vtt |
9.77KB |
| 012 FB Prophet part 1.mp4 |
78.03MB |
| 012 Pandas Subsetting_en.vtt |
6.27KB |
| 012 Pandas Subsetting.mp4 |
22.05MB |
| 012 -------- Regularization ------------.html |
218B |
| 012 Setting up PyTorch Lightning for training_en.vtt |
3.53KB |
| 012 Setting up PyTorch Lightning for training.mp4 |
8.36MB |
| 012 Variational Bayes Linear Classification_en.vtt |
7.51KB |
| 012 Variational Bayes Linear Classification.mp4 |
44.30MB |
| 013 Cross Entropy Loss for Imbalanced Classes_en.vtt |
3.95KB |
| 013 Cross Entropy Loss for Imbalanced Classes.mp4 |
8.50MB |
| 013 FB Prophet part 2_en.vtt |
4.09KB |
| 013 FB Prophet part 2.mp4 |
24.45MB |
| 013 Introduction_en.vtt |
2.62KB |
| 013 Introduction.mp4 |
8.35MB |
| 013 Pandas loc and iloc_en.vtt |
7.62KB |
| 013 Pandas loc and iloc.mp4 |
41.82MB |
| 013 Random Forest theory_en.vtt |
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| 013 Random Forest theory.mp4 |
4.82MB |
| 013 Variational Bayesian Inference Result Analysis_en.vtt |
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| 013 Variational Bayesian Inference Result Analysis.mp4 |
7.37MB |
| 014 Minibatch Variational Bayes_en.vtt |
3.86KB |
| 014 Minibatch Variational Bayes.mp4 |
11.05MB |
| 014 MSE recap_en.vtt |
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| 014 MSE recap.mp4 |
18.30MB |
| 014 Pandas loc and iloc 2_en.vtt |
5.21KB |
| 014 Pandas loc and iloc 2.mp4 |
13.84MB |
| 014 PyTorch Test dataset setup and evaluation_en.vtt |
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| 014 PyTorch Test dataset setup and evaluation.mp4 |
7.10MB |
| 014 Random Forest Code_en.vtt |
6.66KB |
| 014 Random Forest Code.mp4 |
36.74MB |
| 014 Theory behind FB Prophet_en.vtt |
5.89KB |
| 014 Theory behind FB Prophet.mp4 |
16.86MB |
| 015 Deep Bayesian Networks_en.vtt |
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| 015 Deep Bayesian Networks.mp4 |
7.27MB |
| 015 Gradient Boosted Machines_en.vtt |
9.70KB |
| 015 Gradient Boosted Machines.mp4 |
67.61MB |
| 015 L2 Loss Ridge Regression intro_en.vtt |
3.57KB |
| 015 L2 Loss Ridge Regression intro.mp4 |
10.04MB |
| 015 ------------ Model Diagnostics -----.html |
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| 015 Pandas map and apply_en.vtt |
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| 015 Pandas map and apply.mp4 |
31.43MB |
| 015 WandB for logging experiments_en.vtt |
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21.51MB |
| 016 Deep Bayesian Networks - analysis_en.vtt |
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| 016 Deep Bayesian Networks - analysis.mp4 |
10.49MB |
| 016 Overfitting_en.vtt |
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| 016 Overfitting.mp4 |
19.33MB |
| 016 Pandas groupby_en.vtt |
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| 016 Pandas groupby.mp4 |
18.34MB |
| 016 Ridge regression (L2 penalised regression)_en.vtt |
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| 016 Ridge regression (L2 penalised regression).mp4 |
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| 017 Cross Validation_en.vtt |
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| 017 Cross Validation.mp4 |
53.72MB |
| 017 ----- Plotting --------.html |
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| 017 S&P500 data preparation for L1 loss_en.vtt |
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| 017 S&P500 data preparation for L1 loss.mp4 |
25.22MB |
| 018 L1 Penalised Regression (Lasso)_en.vtt |
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| 018 L1 Penalised Regression (Lasso).mp4 |
31.42MB |
| 018 Plotting resources (notebooks).html |
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| 018 Stratified K Fold_en.vtt |
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| 018 Stratified K Fold.mp4 |
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| 019 Area Under Curve (AUC) Part 1_en.vtt |
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| 019 Area Under Curve (AUC) Part 1.mp4 |
84.11MB |
| 019 L1 L2 Penalty theory why it works_en.vtt |
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| 019 L1 L2 Penalty theory why it works.mp4 |
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| 019 Line plot_en.vtt |
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| 019 Line plot.mp4 |
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| 020 Area Under Curve (AUC) Part 2_en.vtt |
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| 020 Area Under Curve (AUC) Part 2.mp4 |
19.50MB |
| 020 Plot multiple lines_en.vtt |
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| 020 Plot multiple lines.mp4 |
45.39MB |
| 021 Histograms_en.vtt |
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| 021 Histograms.mp4 |
21.62MB |
| 022 Scatter Plots_en.vtt |
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| 022 Scatter Plots.mp4 |
18.60MB |
| 023 Subplots_en.vtt |
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| 023 Subplots.mp4 |
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| 024 Seaborn + pair plots_en.vtt |
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