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| Total size: |
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| Archived
files |
|
01 - Working with Sequences\01 - Course Introduction.mp4
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|
01 - Working with Sequences\02 - Sequence data and models.mp4
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73,579,258 |
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|
01 - Working with Sequences\03 - From sequences to inputs.mp4
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28,079,007 |
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01 - Working with Sequences\04 - Modeling sequences with linear models.mp4
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23,442,446 |
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|
01 - Working with Sequences\05 - Getting started with GCP and Qwiklabs.mp4
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|
9,109,776 |
C8B030FF |
|
01 - Working with Sequences\06 - Lab intro -using linear models for sequences.mp4
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|
5,154,528 |
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|
01 - Working with Sequences\07 - Time Series Prediction with a Linear Model.mp4
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|
241,575 |
02CAA3F6 |
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01 - Working with Sequences\08 - Lab solution -using linear models for sequences.mp4
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31,133,853 |
D6C4243A |
|
01 - Working with Sequences\09 - Modeling sequences with DNNs.mp4
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|
24,758,069 |
E66E7363 |
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01 - Working with Sequences\10 - Lab intro -using DNNs for sequences.mp4
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|
5,040,218 |
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|
01 - Working with Sequences\11 - Time Series Prediction with a DNN Model.mp4
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|
240,190 |
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|
01 - Working with Sequences\12 - Lab solution -using DNNs for sequences.mp4
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8,808,878 |
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|
01 - Working with Sequences\13 - Modeling sequences with CNNs.mp4
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30,452,068 |
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|
01 - Working with Sequences\14 - Lab intro -using CNNs for sequences.mp4
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4,947,872 |
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|
01 - Working with Sequences\15 - Time Series Prediction with a CNN Model.mp4
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|
239,460 |
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|
01 - Working with Sequences\16 - Lab solution -using CNNs for sequences.mp4
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12,247,931 |
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|
01 - Working with Sequences\17 - The variable-length problem.mp4
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|
02 - Recurrent Neural Networks\18 - Introducing Recurrent Neural Networks.mp4
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02 - Recurrent Neural Networks\19 - How RNNs represent the past.mp4
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02 - Recurrent Neural Networks\20 - The limits of what RNNs can represent.mp4
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|
02 - Recurrent Neural Networks\21 - The vanishing gradient problem.mp4
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|
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|
03 - Dealing with Longer Sequences\22 - Introduction.mp4
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|
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|
03 - Dealing with Longer Sequences\23 - LSTMs and GRUs.mp4
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|
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|
03 - Dealing with Longer Sequences\24 - RNNs in TensorFlow.mp4
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|
8,532,392 |
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|
03 - Dealing with Longer Sequences\25 - Lab Intro - Time series prediction -end-to-end (rnn).mp4
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|
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|
03 - Dealing with Longer Sequences\26 - Time Series Prediction with a RNN Model.mp4
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03 - Dealing with Longer Sequences\27 - Lab Solution - Time series prediction -end-to-end (rnn).mp4
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39,151,530 |
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|
03 - Dealing with Longer Sequences\28 - Deep RNNs.mp4
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5,118,230 |
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03 - Dealing with Longer Sequences\29 - Lab Intro - Time series prediction -end-to-end (rnn2).mp4
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|
5,410,876 |
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|
03 - Dealing with Longer Sequences\30 - Time Series Prediction with a Two-Layer RNN Model.mp4
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|
250,026 |
29E9C7DF |
|
03 - Dealing with Longer Sequences\31 - Lab Solution - Time series prediction -end-to-end (rnn2).mp4
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|
22,448,918 |
EC0D5FF2 |
|
03 - Dealing with Longer Sequences\32 - Improving our Loss Function.mp4
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|
6,694,422 |
8EBE7093 |
|
03 - Dealing with Longer Sequences\33 - Demo - Time series prediction -end-to-end (rnnN).mp4
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|
12,497,121 |
4C513CA1 |
|
03 - Dealing with Longer Sequences\34 - Working with Real Data.mp4
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|
80,583,771 |
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|
03 - Dealing with Longer Sequences\35 - Lab Intro - Time Series Prediction - Temperature from Weather Data.mp4
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|
10,502,703 |
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|
03 - Dealing with Longer Sequences\36 - An RNN Model for Temperature Data.mp4
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|
239,357 |
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03 - Dealing with Longer Sequences\37 - Lab Solution - Time Series Prediction-Temperature from Weather Data.mp4
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|
52,683,507 |
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|
03 - Dealing with Longer Sequences\38 - Summary.mp4
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|
9,722,783 |
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|
04 - Text Classification\39 - Working with Text.mp4
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|
13,490,184 |
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|
04 - Text Classification\40 - Text Classification.mp4
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|
30,524,564 |
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|
04 - Text Classification\41 - Selecting a Model.mp4
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|
12,271,743 |
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|
04 - Text Classification\42 - Lab Intro - Text Classification.mp4
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|
9,180,930 |
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|
04 - Text Classification\43 - Text Classification using TensorFlow_Keras on AI Platform.mp4
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|
251,730 |
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|
04 - Text Classification\44 - Lab Solution - Text Classification.mp4
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|
43,206,511 |
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|
04 - Text Classification\45 - Python vs Native TensorFlow.mp4
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|
14,636,266 |
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|
04 - Text Classification\46 - Demo -Text Classification with Native TensorFlow.mp4
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|
18,013,196 |
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|
04 - Text Classification\47 - Summary.mp4
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|
12,687,670 |
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|
05 - Reusable Embeddings\48 - Historical methods of making word embeddings.mp4
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|
79,396,691 |
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|
05 - Reusable Embeddings\49 - Modern methods of making word embeddings.mp4
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|
100,037,118 |
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|
05 - Reusable Embeddings\50 - Introducing TensorFlow Hub.mp4
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|
29,522,468 |
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|
05 - Reusable Embeddings\51 - Lab Intro - Evaluating a pre-trained embedding from TensorFlow Hub.mp4
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|
7,725,918 |
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|
05 - Reusable Embeddings\52 - Using pre-trained embeddings with TensorFlow Hub.mp4
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|
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05 - Reusable Embeddings\53 - Lab Solution - TensorFlow Hub.mp4
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40,180,094 |
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|
05 - Reusable Embeddings\54 - Using TensorFlow Hub within an estimator.mp4
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06 - Encoder-Decoder Models\55 - Introducing Encoder-Decoder Networks.mp4
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06 - Encoder-Decoder Models\56 - Attention Networks.mp4
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06 - Encoder-Decoder Models\57 - Training Encoder-Decoder Models with TensorFlow.mp4
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14,870,924 |
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06 - Encoder-Decoder Models\58 - Introducing Tensor2Tensor.mp4
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06 - Encoder-Decoder Models\59 - Lab Intro - Cloud poetry -Training custom text models on Cloud ML Engine.mp4
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4,901,901 |
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06 - Encoder-Decoder Models\60 - Text generation using tensor2tensor on Cloud AI Platform.mp4
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06 - Encoder-Decoder Models\61 - Lab Solution - Cloud poetry -Training custom text models on Cloud ML Engine.mp4
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06 - Encoder-Decoder Models\62 - AutoML Translation.mp4
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06 - Encoder-Decoder Models\63 - Dialogflow.mp4
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|
28,307,181 |
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06 - Encoder-Decoder Models\64 - Lab Intro - Introducing Dialogflow.mp4
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06 - Encoder-Decoder Models\65 - Getting Started with Dialogflow.mp4
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06 - Encoder-Decoder Models\66 - Lab Solution - Dialogflow.mp4
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07 - Summary\67 - Summary.mp4
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|
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|
sequence-models-time-series-natural-language-processing.zip |
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01 - Working with Sequences |
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02 - Recurrent Neural Networks |
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03 - Dealing with Longer Sequences |
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04 - Text Classification |
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05 - Reusable Embeddings |
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06 - Encoder-Decoder Models |
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07 - Summary |
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| Total size: |
1,507,048,870 |
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