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Stone River Elearning – Machine Learning for Apps
Original price was: $99.00.$25.00Current price is: $25.00.
Instant Download: You will receive a download link via your order email immediately
Should you have any questions, please contact us: [email protected]
Stone River Elearning – 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 building apps that can think! In this course you going to learn everything you need to know to building more intelligent apps and your own ML Models.
If you have basic experience with iOS or mobile development then take this course.
Course Curriculum
Introduction to Course
- What is Machine Learning? (7:31)
- Basics of Machine Learning (6:17)
- Installing Anaconda / Python Environment (7:02)
- Downloading / Setting Up Atom & Plugins (8:43)
Python Basics
- Variables in Python (8:07)
- Arrays & Tuples in Python (13:35)
- Functions, Conditionals, & Loops in Python (9:33)
- Importing Modules in Python (5:04)
Building a Classification Model
- What is scikit-learn- Why use it (3:34)
- Installing scikit-learn & scipy with Anaconda (3:11)
- Intro to the Iris Dataset (3:11)
- Datasets- Features & Labels Explained (7:22)
- Loading the Iris Dataset – Examining & Preparing Data (9:10)
- Creating – Training a KNeighborsClassifier (9:25)
- Testing Prediction Accuracy with Test Data (11:47)
- Building Our Own KNeighbors Classifier (17:43)
Building a Convolutional Neural Network
- What is Keras- Why use it (7:44)
- What is a Convolutional Neural Network (CNN) (26:12)
- Installing Keras with Anaconda (4:21)
- Preparing Dataset for a CNN (17:21)
- Building – Visualizing a CNN using Sequential- Part 1 (13:50)
- Building – Visualizing a CNN using Sequential- Part 2 (19:23)
- Training CNN – Evaluating Accuracy – Saving to Disk (17:36)
- Switching Python Environments – Converting to Core ML Model (13:21)
Building a Handwriting Recognition App
- Intro to App – Handwriting (2:38)
- Building Interface – Wiring Up (11:25)
- Drawing On Screen (20:44)
- Importing Core ML Model – Reading Metadata (4:59)
- Utilizing Core ML – Vision to Make Prediction (17:13)
- Handling – Displaying Prediction Results (14:54)
Core ML Basics
- Intro to App – Core ML Photo Analysis (4:08)
- What is Machine Learning (7:31)
- What is Core ML (4:48)
- Creating Xcode Project (2:26)
- Building ImageVC in Interface Builder – Wiring Up (7:23)
- Creating ImageCell & Subclass – Wiring Up (7:55)
- Creating FoodItems Helper File (6:45)
- Creating Custom 3×3 Grid UICollectionViewFlowLayout (8:54)
- Choosing, Downloading, Importing Core ML Model (5:04)
- Passing Images Through Core ML Model (12:01)
- Handling Core ML Prediction Results (9:25)
- Challenge – Core ML Photo Analysis (1:00)
Sale Page: https://stoneriverelearning.com/p/machine-learning-for-apps1
Archive: https://archive.ph/wip/gFqIT
Delivery Method
– After your purchase, you’ll see a View your orders link which goes to the Downloads page. Here, you can download all the files associated with your order.
– Downloads are available once your payment is confirmed, we’ll also send you a download notification email separate from any transaction notification emails you receive from imcourse.info.
– Since it is a digital copy, our suggestion is to download and save it to your hard drive. In case the link is broken for any reason, please contact us and we will resend the new download link.
– If you cannot find the download link, please don’t worry about that. We will update and notify you as soon as possible from 8:00 AM – 8:00 PM (UTC+8).
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