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Build Neural Networks

Machine Learning Intermediate - Linear Algebra for Deep Learning

01 Scalar (4:40)
02 Vector (7:36)
03 Matrix (8:21)
04 Tensor (6:51)
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Machine Learning Intermediate - Matrix Operations

01 Matrix-matrix Addition (4:53)
02 Matrix-scalar Addition (1:59)
03 Matrix-scalar Multiplication (2:06)
04 Matrix Multiplication (2:34)
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Machine Learning Intermediate - Build a Neural Network from Scratch

01 What Is A Neural Network (8:02)
02 Prepare Data (8:31)
03 Shuffle And Batch Data (3:26)
04 Build Weights And Biases (6:25)
05 Build A Neural Network From Scratch (5:28)
06 Optimize The Model (10:20)
07 Train And Evaluate The Model (11:36)
08 Test And Visualize The Neural Network (9:57)
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Machine Learning Intermediate - Build a Convolutional Neural Network from Scratch

01 What Is A Convolutional Neural Network (4:32)
02 Prepare Data For A Convolutional Neural Network (4:09)
03 Shuffle And Batch Data (2:17)
04 Build Weights And Biases (8:48)
05 What Are Wrappers (18:09)
06 Build A Convolutional Neural Network From Scratch (9:57)
07 What Is The Adam Optimizer (13:20)
08 Train And Evaluate The Model (10:32)
09 Test And Visualize The Convolutional Neural Network (7:49)
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Machine Learning Intermediate - Convolutional Neural Networks CIFAR-Image Classification

01 Prepare Data For CIFAR-image Classification (9:48)
02 Normalize Image Values (2:21)
03 Define Classes And Visualize Dataset (8:31)
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04A 2D Convolution Layer (10:14)
04B Relu Activation Function (6:40)
04C 2D Max Pooling Layer (9:34)
04D Flatten And Dense Layers (5:33)
04E Build A CNN For CIFAR-image Classification (13:42)
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05A How Do You Build An Optimizer For CIFAR-image Classification (12:53)
05B How Do You Calculate Loss For CIFAR-image Classification (12:05)
05C Build An Optimizer For CIFAR-image Classification (3:01)
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06 Train The CNN For CIFAR-image Classification (8:20)
07 Evaluate And Visualize The CNN (8:07)
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Machine Learning Intermediate - Build a Recurrent Neural Network

01 What Is A Recurrent Neural Network (4:58)
02 Prepare Data For A Recurrent Neural Network (7:25)
03 Shuffle And Batch Data (2:43)
04 Build A Recurrent Neural Network (7:42)
05 Calculate Accuracy And Loss (4:53)
06 Optimize The Neural Network (5:08)
07 Train A Recurrent Neural Network (6:09)
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Machine Learning Intermediate - Build a Dynamic Recurrent Neural Network

01 What Is A Dynamic Neural Network (6:09)
02 Generate Sample Data (13:39)
03 Shuffle And Batch Data (4:23)
04 Build A Dynamic Neural Network (7:34)
05 Calculate Accuracy And Loss (5:15)
06 Optimize The Neural Network (7:29)
07 Train A Dynamic Neural Network (11:55)
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Machine Learning Intermediate - Build a Bi-directional Recurrent Neural Network

01 What Is A Bi-directional Neural Network (5:46)
02 Prepare Data For A Bi-directional Neural Network (8:54)
03 Build A Bi-directional Neural Network (8:43)
04 Calculate Accuracy And Loss (5:51)
05 Optimize The Bi-directional RNN (5:29)
06 Train A Recurrent Neural Network (6:44)
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Machine Learning Intermediate - Prepare Data For Image Segmentation

01 Load Data For Image Segmentation (6:01)
02 Normalize Images (2:38)
03 Load Training Images (7:11)
04 Load Testing Images (4:38)
05 Prepare Data For Image Segmentation (6:25)
06 Visualize Images And Masks (5:20)
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Machine Learning Intermediate - Build A Neural Network For Image Segmentation

01 How Do You Build A Neural Network For Image Segmentation (10:04)
02 Set Up A Neural Network (6:36)
03 Build Neural Network Layers (6:32)
04 Compile Optimizer And Loss (2:07)
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Machine Learning Intermediate - Train And Test Image Segmentation

01 Build A Mask (1:34)
02 Visualize Model Progress (5:13)
03 Visualize Model Results (13:36)
04 Plot Model Accuracy (7:50)
05 Test The Neural Network (3:37)
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Machine Learning Intermediate - Word2Vec Sentiment Classification of Words

00 What Is Word2vec (5:19)
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Machine Learning Intermediate - Prepare Data for Word2Vec Sentiment Classification

01 Load Data For Word2vec (7:37)
02 Build Datasets For Word2vec (5:56)
03 Cache And Prefetch Data For Word2vec (1:56)
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Machine Learning Intermediate - Build Layers for Word2Vec

00 How Do You Build An Embedding Layer (2:06)
01 Build A Word2vec Embedding Layer (2:35)
02 Clean Data For Word2vec (4:29)
03 How Do You Vectorize Text (10:20)
04 How Do You Build A Word2vec Sequential Layer (27:14)
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Machine Learning Intermediate - Train And Test Word2Vec

01 Optimizer And Loss For Word2vec (2:24)
02 Train And Test The Word2vec Model (2:50)
03 Visualize Word Embeddings (9:02)
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Machine Learning Advanced - Unsupervised Learning Introduction

01 What You'll Learn (5:27)
02 What Is Unsupervised Learning (14:56)
03 Build Models On The Web (5:06)
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Machine Learning Advanced - Build an Auto-Encoder

01 What Is An Auto-encoder (4:44)
02 Prepare Data For An Auto-encoder (10:23)
03 Build Weights And Biases (6:40)
04 Build Encoder And Decoder (6:00)
05 Optimize The Auto-encoder (7:48)
06 Train The Auto-encoder (5:36)
07 Visualize Reconstructed Images (14:15)
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Machine Learning Advanced - Deep Convolutional Generative Adversarial Network

01 What Is A Generative Adversarial Network (8:21)
02 Prepare Data For A Deep Convolutional Generative Adversarial Network (6:48)
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03A Dense Layer (5:04)
03B Batch Normalization Layer (4:07)
03C Leaky ReLu Activation Function (15:55)
03D Transposed Convolution Layer (10:07)
03E Hyperbolic Tangent (tanH) (6:16)
03F Build A Generator (11:15)
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04A How Do You Build A Discriminator (8:22)
04B Build A Discriminator (11:39)
05 Calculate Losses (6:47)
06 Optimize The Deep Convolutional Generative Adversarial Network (12:26)
07 Train The Deep Convolutional Generative Adversarial Network (10:55)
08 Visualize Test Results (8:42)
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Machine Learning Advanced - Image To Image Translation With A GAN

01 Load Data For Image To Image Translation (8:56)
02 Visualize Data For Image To Image Translation (3:31)
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Machine Learning Advanced - Prepare Data For Image To Image Translation

01 Resize Data (2:00)
02 Crop Data (2:15)
03 Diversify Image Data (3:16)
04 Visualize Diversification (3:59)
05 Normalize Image Data (1:28)
06 Load Training Images (2:16)
07 Load Testing Images (2:51)
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Machine Learning Advanced - Build Datasets For Image To Image Translation

01 Build Training Dataset (4:29)
02 Build Testing Dataset (2:48)
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Machine Learning Advanced - Build A Generator For Image To Image Translation

01 Downsample Images (3:58)
02 Upsample Images (4:35)
03 Build A Downstack (3:20)
04 Build An Upstack (3:02)
05 Build More Layers For The Generator (3:31)
06 Downsample Through The Downstack (1:49)
07 Upsample Through The Upstack (3:36)
08 Visualize The Generator (2:50)
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Machine Learning Advanced - Build A Discriminator For Image To Image Translation

01 Build A Discriminator (8:49)
02 Visualize The Discriminator (8:49)
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Machine Learning Advanced - Optimizer and Loss For Image To Image Translation

01 Calculate Generator Loss (4:05)
02 Calculate Discriminator Loss (3:35)
03 Build Optimizers For The GAN (1:32)
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Machine Learning Advanced - Train And Test The GAN

01 Generate Images For The GAN (3:06)
02 Build A Training Step For The GAN (3:06)
03 Train The Gan (5:50)
04 Test The Gan (2:30)
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Source Files

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