Analytics Vidhya

AUGUST 17, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction One of my last articles was all about Convolutional Network, The post Developing an Image Classification Model Using CNN appeared first on Analytics Vidhya.

Modeling 296

Modeling Data Science Publishing Analytics 296

Analytics Vidhya

AUGUST 12, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon Overview This article will briefly discuss CNNs, a special variant. The post A Hands-on Guide to Build Your First Convolutional Neural Network Model appeared first on Analytics Vidhya.

Modeling 343

Modeling Data Science Publishing Analytics 343

Analytics Vidhya

MAY 22, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction In Machine learning or Deep Learning, some of the models. The post How to transform features into Normal/Gaussian Distribution appeared first on Analytics Vidhya.

Deep Learning 304

Deep Learning Machine Learning Data Science Publishing 304

Analytics Vidhya

MAY 22, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction Deep Learning is a very powerful tool that has now. The post Pneumonia Prediction: A guide for your first CNN project appeared first on Analytics Vidhya.

Deep Learning 330

Deep Learning Data Science Publishing Analytics 330

Analytics Vidhya

JULY 7, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon GANs are used for teaching a deep learning model to generate. The post Deep Convolutional Generative Adversarial Network (DCGAN) for Beginners appeared first on Analytics Vidhya.

Deep Learning 266

Deep Learning Data Science Publishing Modeling 266

Analytics Vidhya

JUNE 23, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction Deep neural networks are very fascinating and it produces magic. The post Understanding ResNet and analyzing various models on the CIFAR-10 dataset appeared first on Analytics Vidhya.

Modeling 248

Modeling Data Science Publishing Analytics 248

Analytics Vidhya

APRIL 19, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon. The post Porting a Pytorch Model to C++ appeared first on Analytics Vidhya. Instructions In this article, we are going to see different.

Modeling 204

Modeling Data Science Publishing Analytics 204

Analytics Vidhya

MAY 28, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction If you are a beginner in the field of neural. The post A complete hands-on guide to train your neural network model on Google Colab GPU appeared first on Analytics Vidhya.

Modeling 276

Modeling Data Science Publishing Analytics 276

Analytics Vidhya

MAY 25, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon “Generative Adversarial Networks is the most interesting idea in the last. Train Your First GAN Model | Let’s Talk About GANs Part 2? appeared first on Analytics Vidhya.

Modeling 143

Modeling Data Science Publishing Analytics 143

Analytics Vidhya

JUNE 29, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction Did you developed a Machine Learning or Deep Learning application. The post Deploy Your ML/DL Streamlit Application on Heroku appeared first on Analytics Vidhya.

Deep Learning 155

Deep Learning Machine Learning Data Science Publishing 155

DataRobot

FEBRUARY 10, 2021

Even if all the code runs and the model seems to be spitting out reasonable answers, it’s possible for a model to encode fundamental data science mistakes that invalidate its results. These errors might seem small, but the effects can be disastrous when the model is used to make decisions in the real world.

Modeling 98

Modeling Deep Learning Machine Learning Testing 98

Analytics Vidhya

JUNE 10, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon Yes, it’s true!! Now, object detection models can be done with. The post Simplest way to do Object Detection on custom datasets appeared first on Analytics Vidhya.

Data Science 284

Data Science Publishing Modeling Analytics 284

Data Science and Beyond

DECEMBER 23, 2018

In my opinion it’s more exciting and relevant to everyday life than more hyped data science areas like deep learning. However, I’ve found it hard to apply what I’ve learned about causal inference to my work. Hence, the book is full of practical examples.

Deep Learning 103

Deep Learning Experimentation Data-driven Data Science 103

Analytics Vidhya

APRIL 21, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon. Introduction In the application of the Convolution Neural Network(CNN) model, The post Neural Networks and Activation Function appeared first on Analytics Vidhya.

Data Science 211

Data Science Publishing Modeling Analytics 211

Analytics Vidhya

APRIL 23, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon. Introduction Data models are important in decision-making. programming can. The post Neural Networks Inside Internet Infrastructure appeared first on Analytics Vidhya.

Data Science 188

Data Science Publishing Modeling Analytics 188

Analytics Vidhya

JUNE 11, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction VGG- Network is a convolutional neural network model proposed by. The post Build VGG -Net from Scratch with Python! appeared first on Analytics Vidhya.

Data Science 177

Data Science Publishing Modeling Analytics 177

Rocket-Powered Data Science

DECEMBER 16, 2018

In a related post we discussed the Cold Start Problem in Data Science — how do you start to build a model when you have either no training data or no clear choice of model parameters. There are also examples of cold start in supervised machine learning (where you do have class labels on the training data).

Machine Learning 203

Machine Learning Metrics Optimization Data Science 203

Domino Data Lab

JULY 22, 2019

Paco Nathan presented, “Data Science, Past & Future” , at Rev. At Rev’s “ Data Science, Past & Future” , Paco Nathan covered contextual insight into some common impactful themes over the decades that also provided a “lens” help data scientists, researchers, and leaders consider the future.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

CIO Business Intelligence

AUGUST 11, 2023

How natural language processing works NLP leverages machine learning (ML) algorithms trained on unstructured data, typically text, to analyze how elements of human language are structured together to impart meaning. An NLP algorithm uses this data to find patterns and extrapolate what comes next.

Unstructured Data 142

Unstructured Data Modeling Machine Learning Data mining 142

Sisense

APRIL 10, 2020

One of the most-asked questions from aspiring data scientists is: “What is the best language for data science? People looking into data science languages are usually confused about which language they should learn first: R or Python. NLP can be used on written text or speech data. R or Python?”.

Deep Learning 98

Deep Learning Data Science Machine Learning Visualization 98

O'Reilly on Data

JULY 28, 2020

There’s a substantial literature about ethics, data, and AI, so rather than repeat that discussion, we’ll leave you with a few resources. Ethics and Data Science is a short book that helps developers think through data problems, and includes a checklist that team members should revisit throughout the process.

Marketing 362

Marketing Experimentation Metrics Testing 362

Smart Data Collective

FEBRUARY 15, 2022

In the past, people usually plagiarized content out of books. They would have to go through every possible book they could think of to identify passages that students or other authors might have copied. Towards Data Science has an article dedicated to this topic. “So, So, how do we guard against plagiarism?

Machine Learning 115

Machine Learning Deep Learning Software Technology 115

Occam's Razor

MARCH 30, 2017

People tend to use these phrases almost interchangeably: Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning. Deep Learning is a specific ML technique. Most Deep Learning methods involve artificial neural networks, modeling how our bran works. All sans human-control.

Marketing Analytics 166

Marketing Analytics Marketing Analytics Deep Learning 166

Domino Data Lab

AUGUST 22, 2019

Many thanks to Addison-Wesley Professional for providing the permissions to excerpt “Natural Language Processing” from the book, Deep Learning Illustrated by Krohn , Beyleveld , and Bassens. The excerpt covers how to create word vectors and utilize them as an input into a deep learning model.

Deep Learning 111

Deep Learning Modeling Metrics Testing 111

IBM Big Data Hub

AUGUST 1, 2023

True to their name, generative AI models generate text, images, code , or other responses based on a user’s prompt. But what makes the generative functionality of these models—and, ultimately, their benefits to the organization—possible? That’s where the foundation model enters the picture.

Modeling 59

Modeling Cost-Benefit Data Lake Machine Learning 59

O'Reilly on Data

OCTOBER 19, 2021

Let’s start by considering the job of a non-ML software engineer: writing traditional software deals with well-defined, narrowly-scoped inputs, which the engineer can exhaustively and cleanly model in the code. Not only is data larger, but models—deep learning models in particular—are much larger than before.

IT 346

IT Testing Experimentation Software 346

Domino Data Lab

MAY 8, 2019

Paco Nathan’s latest article features several emerging threads adjacent to model interpretability. I’ve been out themespotting and this month’s article features several emerging threads adjacent to the interpretability of machine learning models. Machine learning model interpretability. Introduction.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

Domino Data Lab

MARCH 3, 2019

Paco Nathan covers recent research on data infrastructure as well as adoption of machine learning and AI in the enterprise. Welcome back to our monthly series about data science! This month, the theme is not specifically about conference summaries; rather, it’s about a set of follow-up surveys from Strata Data attendees.

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

Domino Data Lab

AUGUST 29, 2019

This article provides an excerpt “Deep Reinforcement Learning” from the book, Deep Learning Illustrated by Krohn , Beyleveld , and Bassens. The article includes an overview of reinforcement learning theory with focus on the deep Q-learning. The contents will cover.

Optimization 111

Optimization Modeling Deep Learning Metrics 111

Domino Data Lab

JULY 9, 2019

Chris Wiggins , Chief Data Scientist at The New York Times, presented “Data Science at the New York Times” at Rev. Wiggins also indicated that data science, data engineering, and data analysis are different groups at The New York Times. Session Summary. Transcript. Feel free to email me.

Data Science 112

Data Science Machine Learning Advertising Modeling 112

O'Reilly on Data

JANUARY 25, 2021

This study is based on title usage on O’Reilly online learning. The data includes all usage of our platform, not just content that O’Reilly has published, and certainly not just books. More traditional modes also saw increases: usage of books increased by 11%, while videos were up 24%. AI, Machine Learning, and Data.

Machine Learning 363

Machine Learning Software Testing Technology 363