Understanding U-Net: A Comprehensive Tutorial

U-Net is a convolutional neural network (CNN) architecture designed for semantic segmentation tasks.

Saman .E

2 Min read

In the field of computer vision and image segmentation, U-Net has emerged as a powerful and widely used architecture. U-Net has proven to be highly effective for tasks such as image segmentation, where the goal is to classify each pixel in an image. This tutorial will provide a comprehensive overview of U-Net architecture, its components, and how to implement it for image segmentation tasks. ...

A Comprehensive Guide to Latent Space

Latent space is a lower-dimensional space that captures the essential features of the input data.

Saman .E

2 Min read

In the vast realm of machine learning, the concept of latent space holds a significant position. Latent space is a mathematical representation of data where similar items are grouped, making it a powerful tool for various applications such as image generation, language processing, and more. In this tutorial, we will review the complexities of latent space, exploring its definition, applications, and how it can be leveraged to enhance the capabilities of machine learning models. ...

REINFORCEMENT LEARNING

RL is a type of ML where an agent learns to behave in an environment by trial and error.

Saman .E

3 Min read

Reinforcement learning pipelines are a way to automate the process of training and deploying reinforcement learning agents. They typically consist of the following steps:

Environment, Agent, State, Action, Reward, Policy, Value function, Models, and Hyperparameters. ...

TF-IDF Vs BERT

Both TF-IDF and BERT are integral to modern NLP, enabling the transformation of raw text into structured formats suitable for analysis.

Saman .E

4 Min read

ext feature extraction is the process of converting raw text data into a numerical or structured format that can be used as input for machine learning algorithms, statistical analysis, and various other data-driven tasks. Text data, in its natural form, is challenging for many algorithms to process directly because they typically require numerical input. Feature extraction transforms text data into a more suitable representation while retaining meaningful information. ...

All about Gradio

Gradio is an open-source Python library that simplifies the process of creating custom user interfaces for machine learning models.

Saman .E

4 Min read

When working on machine learning projects, one of the challenges is often how to make the models accessible and usable by users who may not have a technical background. Gradio addresses this challenge by providing a high-level interface that abstracts away the complexities of web development, enabling users to focus on the core functionality of their models. ...