Deep Learning Image classification application- part1 ( Project Overview)

I’ve done self-learning on AI and machine learning for nearly two years and I found out that doing projects is very important for self-learning, because it helps us to solve the real problem and get our hands dirty in the technology that we are learning.

I want to share the process of the project with everyone who just start in AI and ML so you can have a sense of an end to end process of any AI project. I will show you every step in detail from data collection, data preparation, data processing, feature engineering, model training, model deployment, and how to connect any client to the model that I’ve built.

This project, I will divide into 3parts:

1. Project overview and Architecture: I will give an overview of my application, how I built it, and also the technology that will be used in the project
2. Model Training: I will include data collection, data preprocessing, model training using Keras, and transfer learning
3. Model deployment: You can deploy your model by using flask, fast API, or Django, but in my case I want my model to work offline so I will show you how you can convert the model into TensorFlow lite to use in a mobile app.

1. Project Overview

The institute where I study is located on the mountain and in the rainy season there are a lot of mushrooms, and sometimes we want to collect the mushrooms from the forest but…