by Mohamed Elsayed Mohamed Elhaj Abdou | Released November 2018 | ISBN: 9781789340174

Build real-world projects and train them using machine learning algorithms with TensorFlowAbout This VideoUse TensorFlow in real-world scenarios and get confident with using ML Algorithms to build your own projectsUse widely-used TensorFlow packages and tools to explore real-world problems and solve them practicallyBuild projects with ML concepts such as predictive models, classification models, Support Vector Machines, anomaly detection, and Deep Neural NetworksIn DetailMachine learning algorithms and research are mushrooming due to their accuracy at solving problems. This course walks you through developing real-world projects using TensorFlow in your ML projects.The initial project will deal with assessing the viability of expanding your Restaurant business using a single variable linear regression. You will use Linear Regression with multiple variables with an example involving buying and selling a property at the best prices and use a dataset containing 11 features to deal with it. Next, you will create an algorithm to detect anomalous behavior in server computers using Gaussian methods. Finally, you'll design and build a convolutional Neural Networks model on a Traffic Signal Classifier from scratch.By the end of this course you will be using TensorFlow in real-world scenarios, and you'll be confident enough to use ML Algorithms to build your own projects.The code bundle for this video course is available at - https://github.com/PacktPublishing/Real-world-Machine-Learning-Projects-using-TensorFlow Show and hide more

1. Chapter 1 : Getting Started with TensorFlow
   • The Course Overview 00:03:23
   • Installing and Preparing the Environment 00:02:43
   • Installing TensorFlow 00:03:57
   • Warming Up Examples 00:24:58
2. Chapter 2 : Linear Regression with One Variable
   • What Is Machine Learning? 00:05:18
   • Model Representation and Gradient Descent 00:09:47
   • Problem Statement and Solution 00:15:10
3. Chapter 3 : Linear Regression with Multi Variable
   • Model Representation 00:01:47
   • Problem Statement 00:01:17
   • Problem Solution 00:19:32
4. Chapter 4 : Anomaly Detection Algorithm
   • What Is Anomaly Detection? 00:03:51
   • Server Computer's Behavior 00:20:59
5. Chapter 5 : Traffic Sign Classifier
   • Introduction to Traffic Sign Classifier 00:02:13
   • Implementing Traffic Sign Classifier 00:36:53
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