Android 和线性回归 - 房价预测应用程序
Android and Linear Regression - House Price Prediction App
- 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