"Machine Learning for Apps"-Ref.:Udemy.com, Machine Learning, App Development, Development, Programming, Machine Learning for Apps, Machine Learning for App Development

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"Machine Learning for Apps"-Ref.:Udemy.com

Advertiser: Shaw Academy Ltd
Shaw Academy Ltd

" * Start building more intelligent apps with Machine Learning. Take advantage of this new foundational framework! * * What Will I Learn? * Learn to code how the PROs code - not just copy and paste * Build Real Projects - You'll get to build projects that help you retain what you've learned * Build awesome apps that can make predictions * Build amazing apps that can classify human handwriting * * Curriculum For This Course - 42 Lectures * Intro to Course * What is Machine Learning? * Basics of Machine Learning * Installing Anaconda / Python Environment * Downloading / Setting Up Atom & Plugins * Python Basics * Variables in Python * Functions, Conditionals, & Loops in Python * Arrays & Tuples in Python * Importing Modules in Python * Building a Classification Model * What is scikit-learn? Why use it? * Installing scikit-learn & scipy with Anaconda * Intro to the Iris Dataset * Datasets: Features & Labels Explained * Loading the Iris Dataset / Examining & Preparing Data * Creating / Training a KNeighborsClassifier * Testing Prediction Accuracy with Test Data * Building Our Own KNeighborsClassifier * Building a Convolutional Neural Network * What is Keras? Why use it? * What is a Convolutional Neural Network (CNN)? * Installing Keras with Anaconda * Preparing Dataset for a CNN * Building / Visualizing a CNN using Sequential: Part 1 * Building / Visualizing a CNN using Sequential: Part 2 * Training CNN / Evaluating Accuracy / Saving to Disk * Switching Python Environments / Converting to Core ML Model * Building a Handwriting Recognition App * Intro to App – Handwriting * Building Interface / Wiring Up * Drawing On Screen * Importing Core ML Model / Reading Metadata * Utilizing Core ML / Vision to Make Prediction * Handling / Displaying Prediction Results * Core ML Basics * Intro to App – Core ML Photo Analysis * What is Machine Learning? * What is Core ML? * Creating Xcode Project * Building ImageVC in Interface Builder / Wiring Up * Creating ImageCell & Subclass / Wiring Up * Creating FoodItems Helper File * Creating Custom 3x3 Grid UICollectionViewFlowLayout * Choosing, Downloading, Importing Core ML Model * Passing Images Through Core ML Model * Handling Core ML Prediction Results * Challenge – Core ML Photo Analysis * Requirements * Must have a computer with OSX or macOS on it * Description * MACHINE LEARNING FOR APPS * * Welcome to the most comprehensive course on Core ML, one of Apples hot new features for iOS 11. The goal with Machine Learning is to mimic the human mind. It can be used to identify things like objects or images, make predictions and even analyze and identify speech. * * Dive in and learn the core concepts of machine learning and start building apps that can think! In this course you going to learn everything you need to know to start building more intelligent apps and your own ML Models. * * WHY TAKE THIS COURSE? * * Core ML is the first step if you want to start building apps with AI. Machine Learning opens an entirely new world to opportunities that will take your apps to the next level. * * * * Here are some of the things you'll be able to do after taking this course: * * Learn to code how the PROs code - not just copy and paste * Build Real Projects - You'll get to build projects that help you retain what you've learned * Build awesome apps that can make predictions * Build amazing apps that can classify human handwriting * WHAT YOU WILL LEARN: * * Learn about the foundation of Machine Learning and Core ML * Learn foundational python * Build a classification model allow your apps to make predictions * Build a neural network for your app that can classify human writing * Learn core ML concepts so you can build your own ML Model * Utilize the power of Machine Learning and AI for use in iOS apps * Learn how to pass in images to Apples pre trained model - MobileNet * Don't forget to join the free live community where you can get free help anytime from other students * * Who is the target audience? * If you have basic experience with iOS development take this course * If you have basic experience with iOS or mobile development then take this course " - Ref.: Udemy.com

URL: Free-Udemy-Coupon-Code-Gratis-Gratuit-Frei-Gratuito-Kupon-Libre-Gabay-Ders-Bedava-Online-Course-Web-Deal-Discount-Red-Tag-Sale Labels: Free Coupon,Gratis, Gratuit, Frei, Gratuito, Kupon, Libre, Gabay, Ders, Bedava, Online, Course, Web, Deal, Discount Code, Red Tag Sale Reference: https://www.udemy.com/machine-learning-for-apps/?couponCode=FREE_APRIL&deal_code=APR1010

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