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Building Machine Learning Systems with TensorFlow
Exploring and Transforming Data
The Course Overview (3:24)
TensorFlow's Main Data Structure – Tensors (7:14)
Handling the Computing Workflow – TensorFlow's Data Flow Graph (5:25)
Basic Tensor Methods (8:22)
How TensorBoard Works? (5:32)
Reading Information from Disk (4:00)
Clustering
Learning from Data –Unsupervised Learning (2:15)
Mechanics of k-Means (3:34)
k-Nearest Neighbor (5:33)
Project 1 – k-Means Clustering on Synthetic Datasets (4:07)
Project 2 – Nearest Neighbor on Synthetic Datasets (1:52)
Linear Regression
Univariate Linear Modelling Function (4:53)
Optimizer Methods in TensorFlow – The Train Module (3:11)
Univariate Linear Regression (5:10)
Multivariate Linear Regression (5:14)
Logistic Regression
Logistic Function Predecessor – The Logit Functions (4:07)
The Logistic Function (5:53)
Univariate Logistic Regression (6:55)
Univariate Logistic Regression with Keras (2:27)
Simple FeedForward Neural Networks
Preliminary Concepts (7:41)
First Project – Non-Linear Synthetic Function Regression (2:31)
Second Project – Modeling Cars Fuel Efficiency with Non-Linear Regression (3:05)
Third Project – Learning to Classify Wines: Multiclass Classification (2:56)
Convolutional Neural Networks
Origin of Convolutional Neural Networks (3:26)
Applying Convolution in TensorFlow (3:55)
Subsampling Operation – Pooling (2:56)
Improving Efficiency – Dropout Operation (2:15)
Convolutional Type Layer Building Methods (1:02)
MNIST Digit Classification (3:30)
Image Classification with the CIFAR10 Dataset (2:27)
Recurrent Neural Networks and LSTM
Recurrent Neural Networks (3:39)
A Fundamental Component – Gate Operation and Its Steps (4:23)
TensorFlow LSTM Useful Classes and Methods (2:01)
Univariate Time Series Prediction with Energy Consumption Data (2:36)
Writing Music "a la" Bach (8:06)
Deep Neural Networks
Deep Neural Network Definition and Architectures Through Time (2:34)
Alexnet (3:52)
Inception V3 (0:59)
Residual Networks (ResNet) (2:05)
Painting with Style – VGG Style Transfer (3:10)
Library Installation and Additional Tips
Windows Installation (2:38)
MacOS Installation (2:57)
Image Classification with the CIFAR10 Dataset
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