Analytics Vidhya

OCTOBER 28, 2020

This article was published as a part of the Data Science Blogathon. The post What is the Convolutional Neural Network Architecture? Introduction Working on a Project on image recognition or Object Detection but. appeared first on Analytics Vidhya.

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Analytics Vidhya

JULY 23, 2020

Note: This article was originally published on May 29, 2017, and updated on July 24, 2020 Overview Neural Networks is one of the most. The post Understanding and coding Neural Networks From Scratch in Python and R appeared first on Analytics Vidhya.

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Analytics Vidhya

JANUARY 28, 2022

This article was published as a part of the Data Science Blogathon. Introduction Feedforward Neural Networks, also known as Deep feedforward Networks or Multi-layer Perceptrons, are the focus of this article. We’ll do our best to […].

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Analytics Vidhya

MARCH 10, 2022

This article was published as a part of the Data Science Blogathon. Apple’s Siri and Google’s voice search both use Recurrent Neural Networks (RNNs), which are the state-of-the-art method for sequential data. It’s […].

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Analytics Vidhya

APRIL 22, 2024

Introduction Deep learning is a fascinating field that explores the mysteries of gradients and their impact on neural networks. Through vivid visualization and […] The post Exploring Vanishing and Exploding Gradients in Neural Networks appeared first on Analytics Vidhya.

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Analytics Vidhya

MARCH 1, 2022

This article was published as a part of the Data Science Blogathon. Introduction Neural Networks have acquired enormous popularity in recent years due to their usefulness and ease of use in the fields of Pattern Recognition and Data Mining. The post What are Graph Neural Networks, and how do they work?

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Analytics Vidhya

JUNE 18, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon This article explains the problem of exploding and vanishing gradients while. The post The Challenge of Vanishing/Exploding Gradients in Deep Neural Networks appeared first on Analytics Vidhya.

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Analytics Vidhya

NOVEMBER 6, 2020

This article was published as a part of the Data Science Blogathon. The post A Short Intuitive Explanation of Convolutional Recurrent Neural Networks appeared first on Analytics Vidhya. Introduction Hello! Today I am going to try my best in explaining.

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Analytics Vidhya

JANUARY 30, 2022

This article was published as a part of the Data Science Blogathon. The post Activation Functions for Neural Networks and their Implementation in Python appeared first on Analytics Vidhya.

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Analytics Vidhya

OCTOBER 17, 2022

This article was published as a part of the Data Science Blogathon. Introduction Neural networks (Artificial Neural Networks) are methods or algorithms that mimic a human brain’s operations to solve a complex problem that a normal algorithm can’t solve.

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Towards AI

FEBRUARY 11, 2025

Source: Scaler In our ongoing journey to decode the inner workings of neural networks, weve explored the fundamental building blocks the perceptron, MLPs, and weve seen how these models harness the power of activation functions to tackle non-linear problems. The answer lies in loss functions.

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Analytics Vidhya

AUGUST 23, 2021

This article was published as a part of the Data Science Blogathon Building a simple Machine Learning model using Pytorch from scratch. Image by my great learning Introduction Gradient descent is an optimization algorithm that is used to train machine learning models and is now used in a neural network.

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Analytics Vidhya

JULY 8, 2019

Overview Using data science algorithms to generate art and music? The post 8 Simple and Unique Data Science Projects to Create Art, Generate Music and Much More! These 8 AI projects will blow your mind Tap into your creative and artistic. appeared first on Analytics Vidhya.

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Analytics Vidhya

MAY 20, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction Before the sudden rise of neural networks, Support Vector Machines. The post Top 15 Questions to Test your Data Science Skills on SVM appeared first on Analytics Vidhya.

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Analytics Vidhya

OCTOBER 20, 2021

This article was published as a part of the Data Science Blogathon There are many ways a machine can be taught to generate an output on unseen data. we are now at a point where deep learning and neural networks are so powerful that can […].

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Analytics Vidhya

JULY 25, 2022

This article was published as a part of the Data Science Blogathon. It uses Machine Learning-based Model Algorithms and Deep Learning-based Neural Networks for its implementation. […].

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Analytics Vidhya

JANUARY 31, 2022

This article was published as a part of the Data Science Blogathon. Source-Datafloc Introduction Artificial Neural Networks (ANN) have paved a new path to the emerging AI industry since decades it has been introduced.

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IBM Journey to AI blog

JULY 6, 2023

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is data science? This post will dive deeper into the nuances of each field.

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Analytics Vidhya

FEBRUARY 22, 2023

Introduction From the 2000s onward, Many convolutional neural networks have been emerging, trying to push the limits of their antecedents by applying state-of-the-art techniques. The ultimate goal of these deep learning algorithms is to mimic the human eye’s capacity to perceive the surrounding environment.

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Analytics Vidhya

OCTOBER 17, 2022

This article was published as a part of the Data Science Blogathon. Source: Canva Introduction The GoogleAI researchers presented a frame interpolation algorithm synthesising a sharp slow-motion video […].

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Analytics Vidhya

DECEMBER 12, 2022

This article was published as a part of the Data Science Blogathon. Introduction In machine learning and deep learning, the amount of data fed to the algorithm is one of the most critical factors affecting the model’s performance.

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ODSC - Open Data Science

MARCH 12, 2025

The field of data science has evolved dramatically over the past several years, driven by technological breakthroughs, industry demands, and shifting priorities within the community. The Decline of Traditional MachineLearning 20182020: Algorithms like random forests, SVMs, and gradient boosting were frequent discussion points.

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Marktechpost

MARCH 31, 2024

As we enter 2024, the field of data science continues to evolve rapidly, making it essential to stay updated with the latest knowledge and trends. Practical Statistics for Data Scientists This is a beginner-friendly book that covers the statistical concepts that are essential for the field of data science.

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Marktechpost

OCTOBER 10, 2024

In today’s tech-driven world, data science and machine learning are often used interchangeably. This article explores the differences between data science vs. machine learning , highlighting their key functions, roles, and applications. What is Data Science? However, they represent distinct fields.

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Analytics Vidhya

DECEMBER 8, 2021

After all, writing data science articles is from where it all started. Introduction Our long-time followers know how much writing is at the core of this organization. And with each passing year, we have achieved nothing short of miracles with this intention to teach people with our words. At the end of 2021, we are […].

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Unite.AI

NOVEMBER 6, 2023

Traditional machine learning is a broad term that covers a wide variety of algorithms primarily driven by statistics. The two main types of traditional ML algorithms are supervised and unsupervised. These algorithms are designed to develop models from structured datasets. Do We Still Need Traditional Machine Learning Algorithms?

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IBM Journey to AI blog

DECEMBER 20, 2023

Each type and sub-type of ML algorithm has unique benefits and capabilities that teams can leverage for different tasks. ML is a computer science, data science and artificial intelligence (AI) subset that enables systems to learn and improve from data without additional programming interventions.

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Analytics Vidhya

JANUARY 17, 2022

This article was published as a part of the Data Science Blogathon. Introduction A few days ago, I came across a question on “Quora” that boiled down to: “How can I learn Natural Language Processing in just only four months?” ” Then I began to write a brief response.

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Marktechpost

OCTOBER 4, 2024

Time series analysis is a complex & challenging domain in data science, primarily due to the sequential nature and temporal dependencies inherent in the data. Machine Learning Models: This group includes 17 models selected for their ability to handle sequential dependencies within time series data.

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Towards AI

JANUARY 29, 2025

Generative AI is powered by advanced machine learning techniques, particularly deep learning and neural networks, such as Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs). These are essential for understanding machine learning algorithms. Study neural networks, including CNNs, RNNs, and LSTMs.

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Analytics Vidhya

JANUARY 27, 2022

This article was published as a part of the Data Science Blogathon. There are various deep learning algorithms that bring Machine Learning to a new level, allowing robots to learn to discriminate tasks utilizing the human […].

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Analytics Vidhya

MAY 26, 2022

This article was published as a part of the Data Science Blogathon. Introduction Artificial Intelligence has made it possible for machines to learn from experience and adjust to new inputs and perform human-like tasks.

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Unite.AI

SEPTEMBER 4, 2024

Our multi-layered approach combines proprietary algorithms with third-party data to stay ahead of evolving fraud tactics. Deep Neural Network (DNN) Models: Our core infrastructure utilizes multi-stage DNN models to predict the value of each impression or user. The result is a synergy between data science and creativity.

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Artificial Corner

JANUARY 23, 2025

This is what I did when I started learning Python for data science. I checked the curriculum of paid data science courses and then searched all the stuff related to Python. I selected the best 4 free courses I took to learn Python for data science. It makes machine learning model building easy for beginners.

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Data Science Python Convolutional Neural Networks Natural Language Processing 95

NYU Center for Data Science

NOVEMBER 15, 2023

Pinheiro, Joshua Rackers, Joseph Kleinhenz, Michael Maser, *Omar Mahmood (PhD alumnus), Andrew Watkins, Stephen Ra, Vishnu Sresht, Saeed Saremi “A Logic for Expressing Log-Precision Transformers” : *William Merrill (PhD student), Ashish Sabharwal “A Neural Collapse Perspective on Feature Evolution in Graph Neural Networks” : Vignesh Kothapalli, Tom (..)

Data Science 97

Data Science Neural Network Large Language Models Deep Learning 97

IBM Journey to AI blog

JANUARY 10, 2024

Artificial intelligence (AI) refers to the convergent fields of computer and data science focused on building machines with human intelligence to perform tasks that would previously have required a human being. AI operates on three fundamental components: data, algorithms and computing power.

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AI News

OCTOBER 15, 2024

By leveraging vast amounts of data and powerful algorithms, ML enables companies to automate processes, make accurate predictions, and uncover hidden patterns to optimise performance. Unsupervised machine learning systems use artificial neural networks to continue interacting with customers and retain existing customers.

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