deep learning Archives

Basics of Artificial Intelligence: Concept, Brief History, Components

Anum Fatima | June 20, 2024

Artificial intelligence (AI) has evolved from a theoretical concept to a transformative technology impacting various industries. This article guides you through the origins of AI, its initial interpretations, and its progression into machine learning (ML) and deep learning (DL). By understanding these foundational concepts, you’ll be well-prepared to embark on practical projects and delve deeper into the dynamic world of AI and ML. Join me as we unravel the basics and set the stage for hands-on exploration in the fascinating field of artificial intelligence.

Basics of Artificial Intelligence: Concept, Brief History, Components Read More »

Dataset Splitting Train, Validation and Test Sets

How To Choose Train Validation and Test Sets For Your Model?

Anum Fatima | March 7, 2024

In this post, we’ll explore the fundamental concepts of dataset splitting in machine learning. We’ll cover the definitions of train, validation, and test sets, the importance of splitting the dataset, different partitioning strategies, and tips for ensuring proper dataset splitting. Join us as we unravel the keys to effective model development and evaluation.

How To Choose Train Validation and Test Sets For Your Model? Read More »

Overfitting, Underfitting and Model’s Capacity in Deep Learning

Anum Fatima | March 5, 2024

Overfitting, underfitting, and a model’s capacity are critical concepts in deep learning, particularly in the context of training neural networks.

Overfitting, Underfitting and Model’s Capacity in Deep Learning Read More »

Loss Functions for Regression and Classification in Deep Learning

Anum Fatima | March 4, 2024

Loss Functions – Training a neural network is an optimization problem. The goal is to find parameters that minimize this

Loss Functions for Regression and Classification in Deep Learning Read More »

How to Fix the Vanishing Gradient Problem Using ReLU

Anum Fatima | February 21, 2024

Learn how Rectified Linear Unit (ReLU) activation functions can revolutionize your deep neural network training. Discover how ReLU prevents gradients from vanishing, tackles the issue of dying neurons, and explore advanced techniques for optimal performance. Dive into the world of ReLU and unlock the full potential of your neural network models

How to Fix the Vanishing Gradient Problem Using ReLU Read More »

Exploding gradients Problem in Deep Neural Networks

How to Detect Exploding Gradients in Neural Networks

Anum Fatima | February 20, 2024

The exploding gradients occur in a situation opposite to the vanishing gradient problem. Instead of gradients becoming vanishingly small, they

How to Detect Exploding Gradients in Neural Networks Read More »

Vanishing Gradient Problem in Deep Neural Networks

How to Detect Vanishing Gradients in Neural Networks

Anum Fatima | February 19, 2024

Discover the common challenge of vanishing gradients in artificial neural networks and how it impacts the effectiveness of deep learning models. Dive into the root causes of this issue, explore the role of activation functions like sigmoid and tanh, and learn why deep neural networks are particularly susceptible. Uncover strategies to mitigate the vanishing gradient problem and optimize your neural network configurations for improved performance

How to Detect Vanishing Gradients in Neural Networks Read More »

How to Train a Neural Network with Multiple Parameters

Anum Fatima | February 14, 2024

Discover the power of neural networks, complex models inspired by the brain’s design. While single-parameter networks give a basic grasp, real-world tasks need networks with many parameters. Follow along as we simplify the training process, exploring forward and backward steps, using math tricks. Learn practical tips for data prep and model setup to train neural networks effectively.

How to Train a Neural Network with Multiple Parameters Read More »

How to Train a Neural Network with One Parameter

Anum Fatima | February 14, 2024

Learn how to train a neural network with just one parameter, exploring the basics of optimization.
Dive into the process of fine-tuning this single parameter to improve model performance and achieve your goals effectively.

How to Train a Neural Network with One Parameter Read More »