Android & Linear Regression: Train ML models for Android

سرفصل های دوره

Train regression models for Android | Use regression models in Android | Tensorflow Lite models integration in Android

1. Introduction

1. Introduction

2. Machine Learning & Deep Learning Introduction

1. What is Machine Learning

2. Supervised Machine Learning Regression & Classification

3. Unsupervised Machine Learning & Reinforcement Learning

4. Deep Learning and regression models training

5. Basic Deep Learning Concepts

3. Python A simple overview

1. Google Colab

2. Python Introduction & its datatypes

3. Lists in Python

4. Dictionary and Tuples in Python

5. Loops and Conditional Statements in Python

6. File Handling In Python

4. Data Science Libraries Numpy, Pandas, Matplotlib

1. Numpy Library

2. Operations in Numpy

3. Functions in Numpy

4. Pandas library

5. Loading CSV Files in Pandas

6. Handling missing values in Pandas dataset

7. Matplotlib library

8. Images in Matplotlib

5. Tensorflow and Tensorflow Lite

1. Tensorflow Variables & Constants

2. Tensorflow Shapes & Ranks of Tensors

3. Ragged Tesnors & Matrix Multiplication in Tensorflow

4. Tensorflow Operations

5. Random Values in Tensorflow

6. Tensorflow Checkpoints Save ML models

6. Train a simple Regression Model and build Android Application

1. Section Introduction

2. Training a simple regression model for mobile devices

3. Model Testing and Conversion into Tensorflow Lite

4. Tensorflow Lite Model Training Overview

5. Analysing trained tflite model

6. Creating a new Android Studio Project and GUI of Application

7. Adding Tensorflow Lite Library In Android & Loading Tensorflow Lite Model

8. Passing Input to Tensorflow Lite Model in Android and Getting Output

9. Using basic tflite regression model in Android overview

7. Fuel Efficiency Prediction Training an advance regression model

1. Section Introduction

2. Data Collection Finding Fuel Efficiency Prediction Dataset

3. Loading Dataset in Python for Model Training

4. Handling missing Values in Fuel Efficiency Prediction Dataset

5. Handling Categorical Columns in Dataset for Model Training

6. Dataset Normalization

7. Training Fuel Efficiency Prediction Model in Tensorflow

8. Testing Trained Model and converting it to Tensorflow Lite Model

9. Training Fuel Efficiency Prediction Model Overview

8. Fuel Efficiency Prediction Android Application

1. Setting up Android Application for fuel efficiency prediction

2. Starter Application Overview

3. Loading Tensorflow Lite models in Android

4. Data Normalization in Android

5. Passing input to Tensorflow Lite model in Android and getting output

6. Testing fuel efficiency prediction android application

7. Fuel Efficiency Prediction Android App Overview

9. Training a house price prediction Model

1. Section Introduction

2. Getting dataset for training house price prediction model

3. Loading dataset for training tflite model

4. Training & Evaluating house price prediction model

5. Retraining House Price Prediction Model

10. Building House Price Prediction Android Application

1. Setting Up Android Studio Project

2. What we have done so far

3. Data Normalization in Android

4. Passing Input to house price prediction model in Android

5. Testing house price prediction Android Application

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تولید کننده: Udemy