deep learning - Page 6 of 7

What are Convolutional Neural Networks? What can They do?

Convolutional Neural Networks were originally developed by Yann Lecun, who was working at Bell Labs in New Jersey, and Geoffrey Hinton, who was working at the University of Toronto. Convolutional neural networks are a type of deep learning model that is used for image recognition. They use the convolution operation to identify features in images…

How to Solve Underfitting in Machine Learning Models

Underfitting is a common problem in machine learning models. This happens when the model is too simple to capture the complexity of the real data, resulting in poor performance on the training and testing datasets. In this article, we will explore what underfitting is and how to solve it using different techniques. What is Underfitting?…

Overfitting in Machine Learning: What it is and When it Occurs

In machine learning, overfitting refers to the phenomenon where a model performs well with training data, but does not generalize well to new, unseen data. Overfitting occurs when the model is too complex for the amount of training data. To understand overfitting, let’s look at an analogy. Imagine you are in a foreign country and…

Understanding Different Types of Machine Learning: Batch, Online, Instance-Based, and Model-Based Learning

Machine learning is an integral part of artificial intelligence (AI). It allows computer systems to learn from data and improve their performance. There are different types of machine learning, such as batch learning, online learning, example-based learning, and model-based learning. In this article, we will explore each of these types in detail and understand their…

Important Supervised and Unsupervised Algorithms for Machine Learning

Machine learning is a branch of computer science and artificial intelligence that allows machines to learn automatically without special programming. It involves using algorithms and statistical models to analyze and interpret data and make predictions based on that analysis. Machine learning can be broadly divided into two types of algorithms: supervised and unsupervised. In this…

What are the Challenges of Natural Language Processing

Natural Language Processing is that the field of design methods and algorithms that takes as input or produce as output unstructured. Human language is highly ambiguous (consider the sentence I ate pizza with friends, and compare it to I ate pizza with olives), and also highly variable (the core message of I ate pizza with…

Difference between Deep Learning and Natural Language Processing?

In the realm of artificial intelligence, two prominent domains, Deep Learning (DL) and Natural Language Processing (NLP), have emerged as powerful tools. While both are related to machine learning, they serve distinct purposes and possess unique characteristics. This article aims to delve into the dissimilarities between Deep Learning and Natural Language Processing, shedding light on…

What is Image Processing?

Have you ever wanted to change the color of a photo or remove something from your picture? Image processing is what you need! Image processing is the subset of Computer Vision. The transformations we apply on images are sharpening, smoothing, stretching etc. In order to get an enhanced, sharpened, and brighter image, or if we…

What is Deep Learning?

Deep learning is a subset of Machine learning, which in turn is a subset of artificial intelligence, artificial intelligence is a fashion that enables a machine to mimic mortal gets machine learning is a fashion to achieve AI through algorithms trained with data and eventually. deep learning is a type of machine learning inspired by…

Nomidl

Tag: deep learning