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Python and Android TensorFlow Lite - Machine Learning for App Development
Overview
00 Course Overview (3:12)
01 What You'll Need (4:29)
Source files
01 (Prerequisite) Introduction to Machine Learning
00 What Is Python (4:47)
00D What Is Linear Regression (5:03)
01 What Is Machine Learning (5:26)
02 What Is Supervised Learning (11:03)
Source Files
02 Introduction to Python (Prerequisite)
00. Intro To Course And Python (9:57)
01. Variables (19:19)
02. Type Conversion Examples (10:06)
03. Operators (28:54)
04. Collections (8:24)
05. List Examples (19:41)
06. Tuples Examples (8:36)
07. Dictionaries Examples (14:26)
08. Ranges Examples (8:32)
09. Conditionals (6:43)
10. If Statement Examples (21:32)
11. Loops (29:42)
12. Functions (8:04)
13. Parameters And Return Values Examples (13:54)
14. Classes And Objects (34:11)
15. Inheritance Examples (17:29)
16. Static Members Examples (11:05)
17. Summary And Outro (4:08)
03 (Prerequisite) Introduction to Android Studio
00. Introduction (3:26)
01. Downloading And Installing Android Studio (6:53)
02. Exploring Android Studio Interface (12:58)
03. Understanding File Hierarchy (12:19)
04. Exploring Activity-Layout Relationship (19:36)
05. Setting Up An Emulator (7:01)
06. Running App And Implementing User Interaction (6:45)
07. Debugging An App (6:11)
08. Summary And Outro (4:07)
04a (Prerequisite) Introduction to Kotlin
00. Introduction (6:12)
01. Introduction To Variables (7:04)
02. Basic Operations (9:18)
03. Nullable Variables (5:24)
04. Collections Intro (7:27)
05. Mutable Lists And Arrays (6:53)
06. If Statements And Expressions (8:11)
07. When Statements And Expressions (3:30)
08. While Loops (6:46)
09. For In Loops (4:55)
10. Introduction To Functions (7:55)
11. Functions With Parameters And Return Values (7:29)
12. Classes And Objects Introductions (16:37)
13. Subclassing And Superclassing (13:12)
14. Summary And Outro (4:41)
Source FIles
04b Linear regression from scratch
00 Project Preview (2:17)
05 Build a linear regression model with Python for TF Lite
01 Build A Linear Regression Model With Python (15:06)
02 Convert Python Model To Tensorflow Lite (5:38)
Source files
06 Build an Android app with TensorFlow machine learning model
03 Build A New Android Studio App (7:39)
04 Build App Layout (10:18)
Source files
07 Load and use model with Kotlin
05 Load Machine Learning Model (4:53)
06 Use Machine Learning Model (5:17)
07 Connect App Layout To Model (6:08)
Source files
08 Classification
00 Project Preview (1:49)
00 What Is Logistic Regression (4:32)
09 Build a logistic regression model with TensorFlow Keras
01 Load And Process Data For Logistic Regression With Scikit Learn (9:14)
02 Build A Logistic Regression Model With Python (8:01)
03 Convert Logistic Regression Model To Tensorflow Lite (2:38)
Source files
10 Build an Android app with TensorFlow machine learning model
04 Build A New Android Studio App With Tf Lite Model (5:48)
05 Build App Layout For Logistic Regression (9:26)
Source files
11 Load and use model with Kotlin
06 Load Logistic Regression Model In Android Studio (5:01)
07 Use Logistic Regression Model In Android (8:46)
08 Enable App User Interaction With Machine Learning Model (9:53)
Source files
07. Debugging An App
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