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Deep Learning & Neural Networks Python - Keras
Deep Learning & Neural Networks Python - Keras
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Course Overview
Become a trained professional from the safety and comfort of your own home by taking Deep Learning & Neural Networks Python – Keras . Whatever your situation and requirements, One Education can supply you with professional teaching, gained from industry experts, and brought to you for a great price with a limited-time discount.
One Education has been proud to produce an extensive range of best-selling courses, and Deep Learning & Neural Networks Python – Keras is one of our best offerings. It is crafted specially to promote easy learning at any location with an online device. Each topic has been separated into digestible portions that can be memorised and understood in the minimum of time.
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By completing Deep Learning & Neural Networks Python – Keras, you will have automatically earnt an e-certificate that is industry-recognised and will be a great addition to your competencies on your CV.
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Course design
The course is delivered through our online learning platform, accessible through any internet-connected device. There are no formal deadlines or teaching schedules, meaning you are free to study the course at your own pace.
You are taught through a combination of
- Video lessons
- Online study materials
Will I receive a certificate of completion?
Upon successful completion, you will qualify for the UK and internationally-recognised CPD accredited certification. You can choose to make your achievement formal by obtaining your PDF Certificate at the cost of £9 and Hard Copy Certificate for £15.
Why study this course
It doesn’t matter if you are an aspiring professional or absolute beginner; this course will enhance your expertise and boost your CV with critical skills and an accredited certification attesting to your knowledge.
The Deep Learning & Neural Networks Python – Keras is fully available to anyone, and no previous qualifications are needed to enrol. All One Education needs to know is that you are eager to learn and are over 16.
Course Curriculum
| Course Introduction and Table of Contents | |||
| Course Introduction and Table of Contents | 00:11:00 | ||
| Deep Learning Overview | |||
| Deep Learning Overview – Theory Session – Part 1 | 00:06:00 | ||
| Deep Learning Overview – Theory Session – Part 2 | 00:06:00 | ||
| Choosing Between ML or DL for the next AI project - Quick Theory Session | |||
| Choosing Between ML or DL for the next AI project – Quick Theory Session | 00:09:00 | ||
| Preparing Your Computer | |||
| Preparing Your Computer – Part 1 | 00:07:00 | ||
| Preparing Your Computer – Part 2 | 00:06:00 | ||
| Python Basics | |||
| Python Basics – Assignment | 00:09:00 | ||
| Python Basics – Flow Control | 00:09:00 | ||
| Python Basics – Functions | 00:04:00 | ||
| Python Basics – Data Structures | 00:12:00 | ||
| Theano Library Installation and Sample Program to Test | |||
| Theano Library Installation and Sample Program to Test | 00:11:00 | ||
| TensorFlow library Installation and Sample Program to Test | |||
| TensorFlow library Installation and Sample Program to Test | 00:09:00 | ||
| Keras Installation and Switching Theano and TensorFlow Backends | |||
| Keras Installation and Switching Theano and TensorFlow Backends | 00:09:00 | ||
| Explaining Multi-Layer Perceptron Concepts | |||
| Explaining Multi-Layer Perceptron Concepts | 00:03:00 | ||
| Explaining Neural Networks Steps and Terminology | |||
| Explaining Neural Networks Steps and Terminology | 00:10:00 | ||
| First Neural Network with Keras - Understanding Pima Indian Diabetes Dataset | |||
| First Neural Network with Keras – Understanding Pima Indian Diabetes Dataset | 00:07:00 | ||
| Explaining Training and Evaluation Concepts | |||
| Explaining Training and Evaluation Concepts | 00:11:00 | ||
| Pima Indian Model - Steps Explained | |||
| Pima Indian Model – Steps Explained – Part 1 | 00:09:00 | ||
| Pima Indian Model – Steps Explained – Part 2 | 00:07:00 | ||
| Coding the Pima Indian Model | |||
| Coding the Pima Indian Model – Part 1 | 00:11:00 | ||
| Coding the Pima Indian Model – Part 2 | 00:09:00 | ||
| Pima Indian Model - Performance Evaluation | |||
| Pima Indian Model – Performance Evaluation – Automatic Verification | 00:06:00 | ||
| Pima Indian Model – Performance Evaluation – Manual Verification | 00:08:00 | ||
| Pima Indian Model - Performance Evaluation - k-fold Validation - Keras | |||
| Pima Indian Model – Performance Evaluation – k-fold Validation – Keras | 00:10:00 | ||
| Pima Indian Model - Performance Evaluation - Hyper Parameters | |||
| Pima Indian Model – Performance Evaluation – Hyper Parameters | 00:12:00 | ||
| Understanding Iris Flower Multi-Class Dataset | |||
| Understanding Iris Flower Multi-Class Dataset | 00:08:00 | ||
| Developing the Iris Flower Multi-Class Model | |||
| Developing the Iris Flower Multi-Class Model – Part 1 | 00:09:00 | ||
| Developing the Iris Flower Multi-Class Model – Part 2 | 00:06:00 | ||
| Developing the Iris Flower Multi-Class Model – Part 3 | 00:09:00 | ||
| Understanding the Sonar Returns Dataset | |||
| Understanding the Sonar Returns Dataset | 00:07:00 | ||
| Developing the Sonar Returns Model | |||
| Developing the Sonar Returns Model | 00:10:00 | ||
| Sonar Performance Improvement - Data Preparation - Standardization | |||
| Sonar Performance Improvement – Data Preparation – Standardization | 00:15:00 | ||
| Sonar Performance Improvement - Layer Tuning for Smaller Network | |||
| Sonar Performance Improvement – Layer Tuning for Smaller Network | 00:07:00 | ||
| Sonar Performance Improvement - Layer Tuning for Larger Network | |||
| Sonar Performance Improvement – Layer Tuning for Larger Network | 00:06:00 | ||
| Understanding the Boston Housing Regression Dataset | |||
| Understanding the Boston Housing Regression Dataset | 00:07:00 | ||
| Developing the Boston Housing Baseline Model | |||
| Developing the Boston Housing Baseline Model | 00:08:00 | ||
| Boston Performance Improvement by Standardization | |||
| Boston Performance Improvement by Standardization | 00:07:00 | ||
| Boston Performance Improvement by Deeper Network Tuning | |||
| Boston Performance Improvement by Deeper Network Tuning | 00:05:00 | ||
| Boston Performance Improvement by Wider Network Tuning | |||
| Boston Performance Improvement by Wider Network Tuning | 00:04:00 | ||
| Save & Load the Trained Model as JSON File (Pima Indian Dataset) | |||
| Save & Load the Trained Model as JSON File (Pima Indian Dataset) – Part 1 | 00:09:00 | ||
| Save & Load the Trained Model as JSON File (Pima Indian Dataset) – Part 2 | 00:08:00 | ||
| Save and Load Model as YAML File - Pima Indian Dataset | |||
| Save and Load Model as YAML File – Pima Indian Dataset | 00:05:00 | ||
| Load and Predict using the Pima Indian Diabetes Model | |||
| Load and Predict using the Pima Indian Diabetes Model | 00:09:00 | ||
| Load and Predict using the Iris Flower Multi-Class Model | |||
| Load and Predict using the Iris Flower Multi-Class Model | 00:08:00 | ||
| Load and Predict using the Sonar Returns Model | |||
| Load and Predict using the Sonar Returns Model | 00:10:00 | ||
| Load and Predict using the Boston Housing Regression Model | |||
| Load and Predict using the Boston Housing Regression Model | 00:08:00 | ||
| An Introduction to Checkpointing | |||
| An Introduction to Checkpointing | 00:06:00 | ||
| Checkpoint Neural Network Model Improvements | |||
| Checkpoint Neural Network Model Improvements | 00:10:00 | ||
| Checkpoint Neural Network Best Model | |||
| Checkpoint Neural Network Best Model | 00:04:00 | ||
| Loading the Saved Checkpoint | |||
| Loading the Saved Checkpoint | 00:05:00 | ||
| Plotting Model Behavior History | |||
| Plotting Model Behavior History – Introduction | 00:06:00 | ||
| Plotting Model Behavior History – Coding | 00:08:00 | ||
| Dropout Regularization - Visible Layer | |||
| Dropout Regularization – Visible Layer – Part 1 | 00:11:00 | ||
| Dropout Regularization – Visible Layer – Part 2 | 00:06:00 | ||
| Dropout Regularization - Hidden Layer | |||
| Dropout Regularization – Hidden Layer | 00:06:00 | ||
| Learning Rate Schedule using Ionosphere Dataset - Intro | |||
| Learning Rate Schedule using Ionosphere Dataset | 00:06:00 | ||
| Time Based Learning Rate Schedule | |||
| Time Based Learning Rate Schedule – Part 1 | 00:07:00 | ||
| Time Based Learning Rate Schedule – Part 2 | 00:12:00 | ||
| Drop Based Learning Rate Schedule | |||
| Drop Based Learning Rate Schedule – Part 1 | 00:07:00 | ||
| Drop Based Learning Rate Schedule – Part 2 | 00:08:00 | ||
| Convolutional Neural Networks - Introduction | |||
| Convolutional Neural Networks – Part 1 | 00:11:00 | ||
| Convolutional Neural Networks – Part 2 | 00:06:00 | ||
| MNIST Handwritten Digit Recognition Dataset | |||
| Introduction to MNIST Handwritten Digit Recognition Dataset | 00:06:00 | ||
| Downloading and Testing MNIST Handwritten Digit Recognition Dataset | 00:10:00 | ||
| MNIST Multi-Layer Perceptron Model Development | |||
| MNIST Multi-Layer Perceptron Model Development – Part 1 | 00:11:00 | ||
| MNIST Multi-Layer Perceptron Model Development – Part 2 | 00:06:00 | ||
| Convolutional Neural Network Model using MNIST | |||
| Convolutional Neural Network Model using MNIST – Part 1 | 00:13:00 | ||
| Convolutional Neural Network Model using MNIST – Part 2 | 00:12:00 | ||
| Large CNN using MNIST | |||
| Large CNN using MNIST | 00:09:00 | ||
| Load and Predict using the MNIST CNN Model | |||
| Load and Predict using the MNIST CNN Model | 00:14:00 | ||
| Introduction to Image Augmentation using Keras | |||
| Introduction to Image Augmentation using Keras | 00:11:00 | ||
| Augmentation using Sample Wise Standardization | |||
| Augmentation using Sample Wise Standardization | 00:10:00 | ||
| Augmentation using Feature Wise Standardization & ZCA Whitening | |||
| Augmentation using Feature Wise Standardization & ZCA Whitening | 00:04:00 | ||
| Augmentation using Rotation and Flipping | |||
| Augmentation using Rotation and Flipping | 00:04:00 | ||
| Saving Augmentation | |||
| Saving Augmentation | 00:05:00 | ||
| CIFAR-10 Object Recognition Dataset - Understanding and Loading | |||
| CIFAR-10 Object Recognition Dataset – Understanding and Loading | 00:12:00 | ||
| Simple CNN using CIFAR-10 Dataset | |||
| Simple CNN using CIFAR-10 Dataset – Part 1 | 00:09:00 | ||
| Simple CNN using CIFAR-10 Dataset – Part 2 | 00:06:00 | ||
| Simple CNN using CIFAR-10 Dataset – Part 3 | 00:08:00 | ||
| Train and Save CIFAR-10 Model | |||
| Train and Save CIFAR-10 Model | 00:08:00 | ||
| Load and Predict using CIFAR-10 CNN Model | |||
| Load and Predict using CIFAR-10 CNN Model | 00:16:00 | ||
| RECOMENDED READINGS | |||
| Recomended Readings | 00:00:00 | ||
| Order Your Certificate | |||
| Order Your Certificate Now | 00:00:00 | ||
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