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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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    تاریخ انتشار: 27 آذر 1402

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