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Flutter & ML : Train Tensorflow Lite models for Flutter Apps

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Train countless Machine Learning Models for Flutter Application | Use Tensorflow Lite models in Flutter | Flutter ML


1. Introduction
  • 1. Introduction
  • 2. Course Curriculum

  • 2. Machine Learning & Deep Learning
  • 1. Machine Learning Introduction
  • 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 Programming Language
  • 1. Google Colab Introduction
  • 2.1 Python.zip
  • 2. Python Introduction & data types
  • 3. Python Lists
  • 4. Python dictionary & tuples
  • 5. Python loops & conditional statements
  • 6. File handling in Python

  • 4. Data Science Libraries
  • 1.1 DataScience Libraries.zip
  • 1. Numpy Introduction
  • 2. Numpy Operations
  • 3. Numpy Functions
  • 4. Pandas Introduction
  • 5. Loading CSV in pandas
  • 6. Handling Missing values in dataset with pandas
  • 7. Matplotlib & charts in python
  • 8. Dealing images with Matplotlib

  • 5. Tensorflow
  • 1.1 Tensorflow.zip
  • 1. Tensorflow Introduction Variables & Constants
  • 2. Shapes & Ranks of Tensors
  • 3. Matrix Multiplication & Ragged Tensors
  • 4. Tensorflow Operations
  • 5. Generating Random Values in Tensorflow
  • 6. Tensorflow Checkpoints

  • 6. Training a basic regression model
  • 1. Section Introduction
  • 2.1 BasicExample.zip
  • 2. Train a simple regression model for Flutter
  • 3. Testing model and converting it to a tflite(Tensorflow lite) format
  • 4. Model training for flutter overview
  • 5. Creating a new flutter project
  • 6. Adding libraries and loading regression models in Flutter
  • 7. Passing Input to regression model and getting output in Flutter
  • 8. Regression Models Integration in Flutter Overview

  • 7. Training a Fuel Efficiency Prediction Model
  • 1. Section Introduction
  • 2.1 Fuel Efficiency Prediction.zip
  • 2. Getting datasets for training regression models
  • 3. Loading dataset in python with pandas
  • 4. Handling Missing Values in Dataset
  • 5. One Hot Encoding Handling categorical columns
  • 6. Training and testing datasets
  • 7. Normalization Bringing all columns to a common scale
  • 8. Training a fuel efficiency prediction model
  • 9. Testing fuel efficiency prediction model and converting it to a tflite format
  • 10. Fuel Efficiency Model Training Overview

  • 8. Fuel Efficiency Prediction Flutter Application
  • 1. Analyse trained fuel efficiency prediction model
  • 2. Set Up Starter Application for Fuel Efficiency Prediction
  • 3. What we have done so far
  • 4. Loading Tensorflow Lite model in Flutter for fuel efficiency prediction
  • 5. Normalizing user inputs in Flutter before passing it to our model
  • 6. Passing Input to our model and getting output
  • 7. Testing Fuel Efficiency Prediction Flutter Application
  • 8. Fuel Efficiency Prediction Flutter Overview

  • 9. Training House Price Prediction Model
  • 1. Section Introduction
  • 2.1 House Price Prediction.zip
  • 2. Getting house price prediction dataset
  • 3. Load dataset for training house price prediction regression model
  • 4. Training & evaluating house price prediction model
  • 5. Retraining price prediction model

  • 10. House Price Prediction Flutter Application
  • 1. Analysing house price prediction tensorflow lite model
  • 2. Loading house price prediction model in Flutter
  • 3. Passing input to tensorflow lite model and getting output
  • 4. Testing house price prediction Flutter Application
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    تاریخ انتشار: ۲۲ دی ۱۴۰۲
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