3605 Model courses in Leeds delivered On Demand

The course 'Deep Learning & Neural Networks Python - Keras' provides a comprehensive introduction to deep learning using the Keras library in Python. It covers topics ranging from basic neural networks to more advanced concepts, such as convolutional neural networks, image augmentation, and performance improvement techniques for various datasets. Learning Outcomes: Understand the fundamental concepts of deep learning and how it differs from traditional machine learning. Gain proficiency in using Keras, a powerful deep learning library, for building and training neural network models. Develop practical skills in creating and optimizing neural network models for different datasets, including image recognition tasks and regression problems. Why buy this Deep Learning & Neural Networks Python - Keras? Unlimited access to the course for forever Digital Certificate, Transcript, student ID all included in the price Absolutely no hidden fees Directly receive CPD accredited qualifications after course completion Receive one to one assistance on every weekday from professionals Immediately receive the PDF certificate after passing Receive the original copies of your certificate and transcript on the next working day Easily learn the skills and knowledge from the comfort of your home Certification After studying the course materials of the Deep Learning & Neural Networks Python - Keras there will be a written assignment test which you can take either during or at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £5.99. Original Hard Copy certificates need to be ordered at an additional cost of £9.60. Who is this course for? This Deep Learning & Neural Networks Python - Keras course is ideal for Students Recent graduates Job Seekers Anyone interested in this topic People already working in the relevant fields and want to polish their knowledge and skill. Prerequisites This Deep Learning & Neural Networks Python - Keras does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Deep Learning & Neural Networks Python - Keras was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Career path As this course comes with multiple courses included as bonus, you will be able to pursue multiple occupations. This Deep Learning & Neural Networks Python - Keras is a great way for you to gain multiple skills from the comfort of your home. 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 00:07:00 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 00:10:00 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

Overview This comprehensive course on Financial Modelling for Decision Making and Business plan will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Financial Modelling for Decision Making and Business plan comes with accredited certification from CPD, which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast track your career ladder. How will I get my certificate? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. Who is This course for? There is no experience or previous qualifications required for enrolment on this Financial Modelling for Decision Making and Business plan. It is available to all students, of all academic backgrounds. Requirements Our Financial Modelling for Decision Making and Business plan is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. Career Path Learning this new skill will help you to advance in your career. It will diversify your job options and help you develop new techniques to keep up with the fast-changing world. This skillset will help you to- Open doors of opportunities Increase your adaptability Keep you relevant Boost confidence And much more! Course Curriculum 4 sections • 19 lectures • 03:20:00 total length •Introduction to the course: 00:02:00 •Introducton to the Business Priocess: 00:03:00 •What is Financial Modelling: 00:08:00 •Starting Point of a Financial Model: 00:04:00 •First Steps before Starting to create Financial Model and Linking Business Model: 00:07:00 •Starting with End in Mind-Comparative P&L: 00:13:00 •Customer Acquisition Model: 00:16:00 •Revenue and Cost Models: 00:22:00 •Adding Product and Modelling Labour and Other Costs: 00:21:00 •Modelling Capital Investments and ROI Calc: 00:10:00 •Detailed Customer Acquisition Model and Revenue Model: 00:17:00 •Cost of Sale Model: 00:08:00 •Modelling Labour Cost: 00:07:00 •Modelling Other Operating Expenses: 00:14:00 •Modelling Income Statement and Cash Flows: 00:27:00 •Modelling Balance Sheet: 00:14:00 •Fixing the Error in Financial Model and Brief of RR: 00:07:00 •Financial Model for Business plan for New Business: 00:00:00 •Assignment - Financial Modelling for Decision Making and Business plan: 00:00:00

This course covers the fundamental topics of statistical methodology, enabling you to understand the application and interpretation of linear and non-linear regression modeling.

Overview Learn to Create A Selling Strategy that Drives Sales Course is yet another 'Teacher's Choice' course from Teachers Training for a complete understanding of the fundamental topics. You are also entitled to exclusive tutor support and a professional CPD-accredited certificate in addition to the special discounted price for a limited time. Just like all our courses, this Learn to Create A Selling Strategy that Drives Sales Course and its curriculum have also been designed by expert teachers so that teachers of tomorrow can learn from the best and equip themselves with all the necessary skills. Consisting of several modules, the course teaches you everything you need to succeed in this profession. The course can be studied part-time. You can become accredited within 05 Hours studying at your own pace. Your qualification will be recognised and can be checked for validity on our dedicated website. Why Choose Teachers Training Some of our website features are: This is a dedicated website for teaching 24/7 tutor support Interactive Content Affordable price Courses accredited by the UK's top awarding bodies 100% online Flexible deadline Entry Requirements No formal entry requirements. You need to have: Passion for learning A good understanding of the English language Be motivated and hard-working Over the age of 16. Certification CPD Certification from The Teachers Training Successfully completing the MCQ exam of this course qualifies you for a CPD-accredited certificate from The Teachers Training. You will be eligible for both PDF copy and hard copy of the certificate to showcase your achievement however you wish. You can get your digital certificate (PDF) for £4.99 only Hard copy certificates are also available, and you can get one for only £10.99 You can get both PDF and Hard copy certificates for just £12.99! The certificate will add significant weight to your CV and will give you a competitive advantage when applying for jobs. Introduction Importance of a Selling Strategies 00:01:00 Selling Strategies Explained Direct and Indirect Models 00:02:00 Selling Models of Well-Known Companies 00:02:00 Why Selling Strategy Matters 00:03:00 Choosing Your Sales Model 00:02:00 Do a Feasibility Check 00:03:00 What Investors care about 00:01:00 Keys to Success 00:03:00 Additional Selling Strategies 00:05:00 Determine Your Selling Model(s) Determine Your Selling Model - Overview 00:04:00 Selling Model #1 - Online 00:05:00 Selling Model #2 - Retail 00:04:00 Selling Model #3 - Inside/Outside Sales 00:06:00 Selling Model #4 - Distributors 00:03:00 Selling Model #5 - Resellers 00:05:00 Selling Model #6 - Partners or System Integrator 00:05:00 Selling Model #7 - Independent Rep / Manufacturer Rep 00:05:00 Selling Model #8 - OEM / White Label 00:05:00 The Selling Strategy Framework Creating a Selling Strategy Framework 00:08:00 Step 1 - Determine Your Selling Model 00:04:00 Step 2 - Analyzing Your Competition 00:06:00 Step 3 - Examine the Costs 00:06:00 Step 4 - Internal Consistency 00:02:00 Step 5 - Creating Your Selling Strategy 00:08:00 Workshop Workshop: Create Your Selling Strategy 00:04:00 Additional Materials Resource - Learn to Create A Selling Strategy that Drives Sales 00:00:00

Learn to use cutting-edge language models ChatGPT, Dalle-2, and Midjourney to create high-quality written content and generative art in this course. Discover how to fine-tune these models for specific tasks and explore the ethical implications and future-proofing strategies for using AI in your work.

Overview Know the Selling Strategies that Boost Customer Acquisition Course is yet another 'Teacher's Choice' course from Teachers Training for a complete understanding of the fundamental topics. You are also entitled to exclusive tutor support and a professional CPD-accredited certificate in addition to the special discounted price for a limited time. Just like all our courses, this Know the Selling Strategies that Boost Customer Acquisition Course and its curriculum have also been designed by expert teachers so that teachers of tomorrow can learn from the best and equip themselves with all the necessary skills. Consisting of several modules, the course teaches you everything you need to succeed in this profession. The course can be studied part-time. You can become accredited within 05 Hours studying at your own pace. Your qualification will be recognised and can be checked for validity on our dedicated website. Why Choose Teachers Training Some of our website features are: This is a dedicated website for teaching 24/7 tutor support Interactive Content Affordable price Courses accredited by the UK's top awarding bodies 100% online Flexible deadline Entry Requirements No formal entry requirements. You need to have: Passion for learning A good understanding of the English language Be motivated and hard-working Over the age of 16. Certification CPD Certification from The Teachers Training Successfully completing the MCQ exam of this course qualifies you for a CPD-accredited certificate from The Teachers Training. You will be eligible for both PDF copy and hard copy of the certificate to showcase your achievement however you wish. You can get your digital certificate (PDF) for £4.99 only Hard copy certificates are also available, and you can get one for only £10.99 You can get both PDF and Hard copy certificates for just £12.99! The certificate will add significant weight to your CV and will give you a competitive advantage when applying for jobs. Know the Selling Strategies that Boost Customer Acquisition Section 01: Selling Strategies that Boost Customer Acquisition - An Overview Importance of a Selling Strategies 00:01:00 Direct and Indirect Models 00:02:00 Selling Models of Well-Known Companies 00:02:00 Why Selling Strategy Matters 00:03:00 Choosing Your Sales Model 00:02:00 Do a Feasibility Check 00:03:00 What Investors care about 00:01:00 Keys to Success 00:03:00 Additional Selling Strategies 00:05:00 Section 02: Determine the Optimal Sales Channels to Grow your Business Importance of a Selling Strategies 00:01:00 Determine Your Selling Model - Overview 00:04:00 Selling Model #1 - Online 00:05:00 Selling Model #2 - Retail 00:04:00 Selling Model #3 - Inside/Outside Sales 00:06:00 Selling Model #4 - Distributors 00:03:00 Selling Model #5 - Resellers 00:05:00 Selling Model #6 - Partners or System Integrator 00:05:00 Selling Model #7 - Independent Rep / Manufacturer Rep 00:05:00 Selling Model #8 - OEM / White Label 00:05:00 Section 03: Create a Selling Strategy for Your Business Importance of a Selling Strategies 00:01:00 Creating a Selling Strategy Framework 00:08:00 Step 1 - Determine Your Selling Model 00:04:00 Step 2 - Analyzing Your Competition 00:06:00 Step 3 - Examine the Costs 00:06:00 Step 4 - Internal Consistency 00:02:00 Step 5 - Creating Your Selling Strategy 00:08:00 Support Materials Resource - Know the Selling Strategies that Boost Customer Acquisition 00:00:00

This comprehensive course will help you learn the basics to advanced mechanisms of chatbot development using deep learning with Python. This course is a complete package for beginners to learn chatbot fundamentals with deep learning and its applications and build it from scratch using deep learning (RNNs) with Python.

Innovation Project Management: On-Demand Companies need growth for survival. Companies cannot grow simply through cost reduction and reengineering efforts. This program describes the relationship that needs to be established between innovation, business strategy, and project management to turn a creative idea into a reality. We will explore the importance of identifying the components of an innovative culture, existing differences, challenges, and the new set of skills needed in innovation project management. Companies need growth for survival. Companies cannot grow simply through cost reduction and reengineering efforts. Innovation is needed and someone must manage these innovation projects. Over the past two decades, there has been a great deal of literature published on innovation and innovation management. Converting a creative idea into reality requires projects and some form of project management. Unfortunately, innovation projects, which are viewed as strategic projects, may not be able to be managed using the traditional project management philosophy we teach in our project management courses. There are different skill sets needed, different tools, and different life-cycle phases. Innovation varies from industry to industry and even companies within the same industry cannot come to an agreement on how innovation project management should work. This program describes the relationship that needs to be established between innovation, business strategy, and project management to turn a creative idea into a reality. We will explore the importance of identifying the components of an innovative culture, existing differences, challenges, and the new set of skills needed in innovation project management. What you Will Learn Explain the links needed to bridge innovation, project management, and business strategy Describe the different types of innovation and the form of project management each require Identify the differences between traditional and innovation project management, especially regarding governance, human resources management challenges, components of an innovative culture and competencies needed by innovation project managers Establish business value and the importance of new metrics for measuring and reporting business value Relate innovation to business models and the skills needed to contribute in the business model development Recognize the roadblocks affecting innovation project management and their cause to determine what actions can be taken Determine the success and failure criteria of an innovation project Foundation Concepts Understanding innovation Role of innovation in a company Differences between traditional (operational) and strategic projects Innovation management Differences between innovation and R&D Differing views of innovation Why innovation often struggles Linking Innovation Project Management to Business Strategy The business side of innovation project management The need for innovation targeting Getting close to the customers and their needs The need for line-of-sight to the strategic objectives The innovation enterprise environmental factors Tools for linking Internal Versus External (Co-creation) Innovation Open versus closed innovation Open innovation versus crowdsourcing Benefits of internal innovation Benefits of co-creation (external) innovation Selecting co-creation partners The focus of co-creation The issues with intellectual property Understanding co-creation values Understanding the importance of value-in-use Classification of Innovations and Innovation Projects Types of projects Types of innovations Competency-enhancing versus competency-destroying innovations Types of innovation novelty Public Sector of Innovation Comparing public and private sector project management Types of public service innovations Reasons for some public sector innovation failures An Introduction to Innovation Project Management Why traditional project management may not work The need for a knowledge management system Differences between traditional and innovation project management Issues with the 'one-size-fits-all' methodology Using end-to-end innovation project management Technology readiness levels (TRLs) Integrating Kanban principles into innovation project management Innovation and the Human Resources Management Challenge Obtaining resources Need for a talent pipeline Need for effective resource management practices Prioritizing resource utilization Using organizational slack Corporate Innovation Governance Types of innovation governance Business Impact Analysis (BIA) Innovation Project Portfolio Management Office (IPPMO) Using nondisclosure agreements, secrecy agreements, confidentiality agreements, and patents Adverse effects of governance decisions Innovation Cultures Characteristics of a culture for innovation Types of cultures Selecting the right people Linking innovation to rewards Impact of the organizational reward system Innovation Competencies Types of innovation leadership The need for active listening Design thinking Dealing with ambiguity, uncertainty, risks, crises, and human factors Value-Based Innovation Project Management Metrics Importance of innovation project management metrics Understanding value-driven project management Differences between benefits and value - and when to measure Traditional versus the investment life cycle Benefits harvesting Benefits and value sustainment Resistance to change Tangible and intangible innovation project management metrics Business Model Innovation Business model characteristics Impact of disruptive innovation Innovation Roadblocks Roadblocks and challenges facing project managers Ways to overcome the roadblocks Defining Innovation Success and Failure Categories for innovation success and failure Need for suitability and exit criteria Reasons for innovation project failure Predictions on the Future of Innovation Project Management The Six Pillars of changing times Some uses for the new value and benefits metrics

Learn to apply sentiment analysis to your problems through a practical, real-world use case.

Overview This Deep Learning & Neural Networks Python - Keras: For Dummies course will unlock your full potential and will show you how to excel in a career in Deep Learning & Neural Networks Python - Keras: For Dummies. So upskill now and reach your full potential. Everything you need to get started in Deep Learning & Neural Networks Python - Keras: For Dummies is available in this course. Learning and progressing are the hallmarks of personal development. This Deep Learning & Neural Networks Python - Keras: For Dummies will quickly teach you the must-have skills needed to start in the relevant industry. In This Deep Learning & Neural Networks Python - Keras: For Dummies Course, You Will: Learn strategies to boost your workplace efficiency. Hone your Deep Learning & Neural Networks Python - Keras: For Dummies skills to help you advance your career. Acquire a comprehensive understanding of various Deep Learning & Neural Networks Python - Keras: For Dummies topics and tips from industry experts. Learn in-demand Deep Learning & Neural Networks Python - Keras: For Dummies skills that are in high demand among UK employers, which will help you to kickstart your career. This Deep Learning & Neural Networks Python - Keras: For Dummies course covers everything you must know to stand against the tough competition in the Deep Learning & Neural Networks Python - Keras: For Dummies field.  The future is truly yours to seize with this Deep Learning & Neural Networks Python - Keras: For Dummies. Enrol today and complete the course to achieve a Deep Learning & Neural Networks Python - Keras: For Dummies certificate that can change your professional career forever. Additional Perks of Buying a Course From Institute of Mental Health Study online - whenever and wherever you want. One-to-one support from a dedicated tutor throughout your course. Certificate immediately upon course completion 100% Money back guarantee Exclusive discounts on your next course purchase from Institute of Mental Health Enrolling in the Deep Learning & Neural Networks Python - Keras: For Dummies course can assist you in getting into your desired career quicker than you ever imagined. So without further ado, start now. Process of Evaluation After studying the Deep Learning & Neural Networks Python - Keras: For Dummies course, your skills and knowledge will be tested with a MCQ exam or assignment. You must get a score of 60% to pass the test and get your certificate.  Certificate of Achievement Upon successfully completing the Deep Learning & Neural Networks Python - Keras: For Dummies course, you will get your CPD accredited digital certificate immediately. And you can also claim the hardcopy certificate completely free of charge. All you have to do is pay a shipping charge of just £3.99. Who Is This Course for? This Deep Learning & Neural Networks Python - Keras: For Dummies is suitable for anyone aspiring to start a career in Deep Learning & Neural Networks Python - Keras: For Dummies; even if you are new to this and have no prior knowledge on Deep Learning & Neural Networks Python - Keras: For Dummies, this course is going to be very easy for you to understand.  And if you are already working in the Deep Learning & Neural Networks Python - Keras: For Dummies field, this course will be a great source of knowledge for you to improve your existing skills and take them to the next level.  Taking this Deep Learning & Neural Networks Python - Keras: For Dummies course is a win-win for you in all aspects.  This course has been developed with maximum flexibility and accessibility, making it ideal for people who don't have the time to devote to traditional education. Requirements This Deep Learning & Neural Networks Python - Keras: For Dummies course has no prerequisite.  You don't need any educational qualification or experience to enrol in the Deep Learning & Neural Networks Python - Keras: For Dummies course. Do note: you must be at least 16 years old to enrol. Any internet-connected device, such as a computer, tablet, or smartphone, can access this online Deep Learning & Neural Networks Python - Keras: For Dummies course. Moreover, this course allows you to learn at your own pace while developing transferable and marketable skills. 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 00:07:00 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 00:10:00 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