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TensorFlow and the Google Cloud ML Engine for Deep Learning
You, This Course and Us
You, This Course and Us
Source Code and PDFs
Datasets for all Labs
Installation
Install TensorFlow
Install Jupyter Notebook
Running on the GCP vs. Running on your local machine
Lab: Setting Up A GCP Account
Lab: Using The Cloud Shell
Datalab ~ Jupyter
Lab: Creating And Working On A Datalab Instance
TensorFlow and Machine Learning
Introducing Machine Learning
Representation Learning
Neural Networks Introduced
Introducing TensorFlow
Running on the GCP vs. Running on your local machine
Lab: Simple Math Operations
Computation Graph
Tensors
Lab: Tensors
Linear Regression Intro
Placeholders and Variables
Lab: Placeholders
Lab: Variables
Lab: Linear Regression with Made-up Data
Quiz 1: TensorFlow Basics
Working with Images
Image Processing
Images As Tensors
Lab: Reading and Working with Images
Lab: Image Transformations
Quiz 2: Images
K-Nearest-Neighbors with TensorFlow
Introducing MNIST
K-Nearest Neigbors as Unsupervised Learning
One-hot Notation and L1 Distance
Steps in the K-Nearest-Neighbors Implementation
Lab: K-Nearest-Neighbors
Quiz 3: MNIST with K-Nearest Neighbors
Linear Regression with a Single Neuron
Learning Algorithm
Individual Neuron
Learning Regression
Learning XOR
XOR Trained
Linear Regression in TensorFlow
Lab: Access Data from Yahoo Finance
Non TensorFlow Regression
Lab: Linear Regression - Setting Up a Baseline
Gradient Descent
Lab: Linear Regression
Lab: Multiple Regression in TensorFlow
Quiz 4: Linear Regression
Logistic Regression in TensorFlow
Logistic Regression Introduced
Linear Classification
Lab: Logistic Regression - Setting Up a Baseline
Logit
Softmax
Argmax
Lab: Logistic Regression
Quiz 5: Logistic Regression
The Estimator API
Estimators
Lab: Linear Regression using Estimators
Lab: Logistic Regression using Estimators
Quiz 6: Estimators
Neural Networks and Deep Learning
Traditional Machine Learning
Deep Learning
Operation of a Single Neuron
The Activation Function
Training a Neural Network: Back Propagation
Lab: Automobile Price Prediction - Exploring the Dataset
Lab: Automobile Price Prediction - Using TensorFlow for Prediction
Hyperparameters
Vanishing and Exploding Gradients
The Bias-Variance Trade-off
Preventing Overfitting
Lab: Iris Flower Classification
Quiz 7: Neural Networks and Deep Learning
Classifiers and Classification
Classification as an ML Problem
Confusion Matrix: Accuracy, Precision and Recall
Decision Thresholds and The Precision-Recall Trade-off
F1 Scores and The ROC Curve
Quiz 8: Classification
Convolutional Neural Networks (CNNs)
Mimicking the Visual Cortex
Convolution
Choice of Kernel Functions
Zero Padding and Stride Size
CNNs vs DNNs
Feature Maps
Pooling
Lab: Classification of Street View House Numbers - Exploring the Dataset
Basic Architecture of a CNN
Lab: Classification of Street View House Numbers - Building the Model
Lab: Classification of Street View House Numbers - Running the Model
Lab: Building a CNN Using the Estimator API
Quiz 9: Convolutional Neural Networks (CNNs)
Recurrent Neural Networks (RNNs)
Learning From the Past
Unrolling an RNN Cell Through Time
Training an RNN - Back Propagation Through Time
Lab: RNNs for Image Classifcation
Vanishing and Exploding Gradients in an RNN
Long Memory Neurons vs Truncated BPTT
The Long/Short Term Memory Cell
A Sequence of Words
Text in Numeric Form
Lab: Sentiment Analysis on Rotten Tomatoes Reviews - Exploring the Dataset
Lab: Sentiment Analysis on Rotten Tomatoes Reviews - Building, Running the Model
Quiz 10: Recurrent Neural Networks (RNNs)
Unsupervised Learning
Supervised and Unsupervised Learning
Expressing Attributes as Numbers
K-Means Clustering
Lab: K-Means Clustering with 2-Dimensional Points in Space
Lab: K-Means Clustering with Images
Patterns in Data
Principal Components Analysis
Autoencoders
Autoencoder Neural Network Architecture
Lab: PCA on Stock Data - Matplotlib vs Autoencoders
Stacked Autoencoders
Lab: Stacked Autoencoder With Dropout
Lab: Stacked Autoencoder With Regularization and He Initialization
Denoising Autoencoders
Lab: Denoising Autoencoder with Gaussian Noise
Quiz 11: Unsupervised Learning
TensorFlow on the Google Cloud
Running TensorFlow on the Cloud
Lab: Taxicab Prediction - Setting up the dataset
Lab: Taxicab Prediction - Training and Running the model
Quiz 12: GCP Basics
TensorFlow Using Cloud ML Engine
A Taxicab Fare Prediction Problem
Datalab
Querying BigQuery
Explore Data
Clean Data
Benchmark
Using TensorFlow
The Estimator API
The Experiment Function
Introduction to Cloud MLE
Using Cloud MLE
The Training Service
The Prediction Service
Quiz 13: Cloud ML Engine
Feature Engineering and Hyperparameter Tuning
Feature Engineering to the rescue
New Approach
Dataflow Create Pipeline
Dataflow Run Pipeline
Feature Engineering
Deep And Wide Models
Hyperparameter Tuning
Hyperparameter Tuning on the GCP
Quiz 14: Feature Engineering and Hyperparameter Tuning
Classification as an ML Problem
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