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Mobile Machine Learning with CoreML: Artificial Intelligence iOS 14 and Swift 5 Masterclass
00a (Prerequisite) Swift Language Basics
00. Language Basics Topics List (4:55)
(Prerequisite) 01. Variable and Constants
00. Learning Goals (3:59)
01. Intro To Variables And Constants (15:51)
02. Primitive Types (18:42)
03. Strings (18:45)
04. Nil Values (12:50)
05. Tuples (14:14)
06. Type Conversions (23:14)
07. Assignment Operators (11:18)
08. Conditional Operators (12:26)
Variables and Constants Text.playground
(Prerequisite) 02. Collection Types
00. Topics List And Learning Objectives (3:11)
01. Intro To Collection Types (10:32)
02. Creating Arrays (4:53)
03. Common Array Operations (25:01)
04. Multidimensional Arrays (7:38)
05. Ranges (9:34)
Collection Types Text.playground
(Prerequisite) 03. Control flow
00. Topics List And Learning Objectives (3:40)
01. Intro To If And Else Statements (9:41)
02. Else If Statements (8:47)
03. Multiple Simultaneous Tests (12:32)
04. Intro To Switch Statements (9:21)
05. Advanced Switch Statement Techniques (15:59)
06. Testing For Nil Values (11:49)
07. Intro To While Loops (14:25)
08a. Intro To For...in Loops (14:13)
08b Intro To For...in Loops (cont'd) (10:53)
09. Complex Loops And Loop Control Statements (19:39)
Control Flow Text.playground
(Prerequisite) 04. Functions
00. Topics List And Learning Objectives (3:50)
01. Intro To Functions (19:54)
02. Function Parameters (11:35)
03. Return Statements (14:00)
04a. Parameter Variations - Argument Labels (8:57)
04b. Parameter Variations - Default Values (5:24)
04c. Parameters Variations - Inout Parameters (8:37)
04d. Parameter Variations - Variadic Parameters (10:46)
05. Returning Multiple Values Simultaneously (7:21)
Functions Text.playground
(Prerequisite) 05. Classes, Struct and Enums
00. Topics List And Learning Objectives- (4:59)
01. Intro To Classes (15:58)
02A. Properties As Fields - Add To Class Implementation (13:17)
02B. Custom Getters And Setters (8:18)
02C. Calculated Properties (23:46)
02D. Variable Scope And Self (12:49)
02E. Lazy And Static Variables (14:09)
03A. Behaviour And Instance Methods (16:12)
03B. Class Type Methods (7:17)
04. Class Instances As Field Variables (8:26)
05A. Inheritance, Subclassing And Superclassing (23:41)
05B. Overriding Initializers (13:16)
05C. Overriding Properties (16:04)
05D. Overriding Methods (10:08)
06. Structs Overview (19:58)
07. Enumerations (16:05)
08. Comparisons Between Classes, Structs And Enums (14:14)
Classes, Structs, Enums Text.playground
00b (Prerequisite) Introduction to Xcode
00. Intro And Demo (6:28)
01. General Interface Intro (14:40)
02. File System Introduction (12:59)
03. Viewcontroller Intro (6:28)
04. Storyboard File Intro (17:03)
05. Connecting Outlets And Actions (13:47)
06. Running An Application (9:40)
07. Debugging An Application (11:15)
XCode Intro
00c CoreML Overview
01 What Is Coreml (6:46)
Source Files
01 Course Overview
01 What You'll Learn (5:24)
Source Files
02 Natural Language Framework
Source Files
01 Natural Language Framework (4:30)
03. Text Analysis with the Natural Language Framework
01 Project Setup (7:26)
02 Recognize Dominant Language Of A Text (7:51)
03 What Is String Tokenization (4:13)
04 Tokenize A String (7:22)
05 Identify Parts Of Speech (10:26)
06 Identify People, Places And Organizations (14:26)
Source Files
04 Find Similarities Between Pieces of Text
01 What Is Word Embedding (7:36)
02 Find Similar Words (6:18)
03 Find Word Neighbors (8:34)
04 Find Similar Sentences (9:00)
Source Files
05 Train Sentiment Analysis with CreateML
00 What Is Sentiment Analysis (4:38)
01 Gather Dataset (6:59)
02 Train A Model In CreateML (11:18)
03 Use The Model In An App (10:25)
Source Files
06a Build An Image Classifier With Create ML
01 Train Image Classification In Create Ml (10:33)
02 Evaluate And Save The Image Classification Model (2:30)
03 Set Up App For Image Classification (5:55)
04 Process Images For Image Classification (11:24)
05 Use The Image Classification Model In An App (8:41)
Source Files
06b Build A Linear Regressor from CSV Data
00 What Is Linear Regression (4:48)
01 Gather Data For Linear Regressor (11:48)
Source Files
06c Build A Classifier from CSV Data
01 Gather Data For Classifier (8:23)
02 Train The Classifier (16:02)
Source Files
07 Object Detection with MobileNetV2
01 Mobilenetv2 Project Setup (5:56)
02 Download And Import The Model (7:49)
03 Resize Images (5:00)
04 Make A Pixel Buffer (5:43)
05 Make Rgb Color Space (5:11)
06 Make A Prediction (14:11)
Source Files
08 Image Recognition with YOLOv3
01 Yolov3 Project Setup (3:23)
02 Download The Yolov3 Model (6:53)
03 Resize Images (3:38)
04 Make A Pixel Buffer (4:40)
05 Make Rgb Color Space (3:54)
06 Make A Prediction (13:39)
Source Files
02 Recognize Dominant Language Of A Text
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