Analytics Vidhya

FEBRUARY 12, 2024

Introduction Pie charts, a widely used visualization tool, represent data proportions in a circular format. Each slice corresponds to a category, facilitating quick comparisons. Importance of Pie Charts in Data Visualization Pie charts play a crucial role in data visualization for several reasons.

Data Visualization 258

Data Visualization Analytics Analytics Python 258

Analytics Vidhya

DECEMBER 20, 2023

Introduction Data augmentation encompasses various techniques to expand and enhance datasets for machine learning and deep learning models. These methods span different categories, each altering data to introduce diversity and improve model robustness.

Deep Learning 277

Deep Learning Deep Learning Machine Learning Machine Learning 277

insideBIGDATA

NOVEMBER 14, 2023

In this column, we present a variety of short time-critical news items grouped by category such as M&A activity, people movements, funding news, financial results, industry alignments, customer wins, rumors and general scuttlebutt floating around the big data, data science and machine learning industries including behind-the-scenes anecdotes and (..)

Big Data 259

Big Data Big Data Machine Learning Machine Learning 259

insideBIGDATA

MARCH 4, 2024

Hammerspace, the company orchestrating the Next Data Cycle, unveiled the high-performance NAS architecture needed to address the requirements of broad-based enterprise AI, machine learning and deep learning (AI/ML/DL) initiatives and the widespread rise of GPU computing both on-premises and in the cloud.

Deep Learning 221

Deep Learning Deep Learning Clustering Machine Learning 221

KDnuggets

APRIL 7, 2022

According to one source, the types of questions that will generally be asked in data scientist interviews can be broken down into five categories. Let's take a closer look.

Data Science 397

Data Science Data Scientist 397

insideBIGDATA

SEPTEMBER 29, 2023

In this column, we present a variety of short time-critical news items grouped by category such as M&A activity, people movements, funding news, financial results, industry alignments, customer wins, rumors and general scuttlebutt floating around the big data, data science and machine learning industries including behind-the-scenes anecdotes and (..)

Big Data 243

Big Data Big Data Machine Learning Machine Learning 243

Analytics Vidhya

FEBRUARY 15, 2024

Introduction Data visualization is a crucial aspect of data analysis, aiding in comprehending and communicating complex datasets. Among the myriad visualization techniques available, area charts stand out for effectively representing quantitative data over time or categories.

Python 261

Python Data Visualization Data Analysis Data Analysis 261

insideBIGDATA

MARCH 31, 2023

In this column, we present a variety of short time-critical news items grouped by category such as M&A activity, people movements, funding news, financial results, industry alignments, customer wins, rumors and general scuttlebutt floating around the big data, data science and machine learning industries including behind-the-scenes anecdotes and (..)

Big Data 307

Big Data Big Data Machine Learning Machine Learning 307

insideBIGDATA

FEBRUARY 2, 2023

In this column, we present a variety of short time-critical news items grouped by category such as M&A activity, people movements, funding news, financial results, industry alignments, customer wins, rumors and general scuttlebutt floating around the big data, data science and machine learning industries including behind-the-scenes anecdotes and (..)

Big Data 317

Big Data Big Data Machine Learning Machine Learning 317

Analytics Vidhya

JANUARY 13, 2023

This article was published as a part of the Data Science Blogathon. Introduction This is a multiclass classification project to classify the severity of road accidents into three categories. This project is based on real-world data, and the dataset is also highly imbalanced.

Machine Learning 347

Machine Learning Machine Learning Data Science Analytics 347

insideBIGDATA

DECEMBER 20, 2023

In this column, we present a variety of short time-critical news items grouped by category such as M&A activity, people movements, funding news, financial results, industry alignments, customer wins, rumors and general scuttlebutt floating around the big data, data science and machine learning industries including behind-the-scenes anecdotes and (..)

Big Data 195

Big Data Big Data Machine Learning Machine Learning 195

insideBIGDATA

FEBRUARY 28, 2023

In this column, we present a variety of short time-critical news items grouped by category such as M&A activity, people movements, funding news, financial results, industry alignments, customer wins, rumors and general scuttlebutt floating around the big data, data science and machine learning industries including behind-the-scenes anecdotes and (..)

Big Data 293

Big Data Big Data Machine Learning Machine Learning 293

insideBIGDATA

JUNE 21, 2023

In this column, we present a variety of short time-critical news items grouped by category such as M&A activity, people movements, funding news, financial results, industry alignments, customer wins, rumors and general scuttlebutt floating around the big data, data science and machine learning industries including behind-the-scenes anecdotes and (..)

Big Data 243

Big Data Big Data Machine Learning Machine Learning 243

Data Science Dojo

MAY 29, 2023

Unlock the full potential of your data with the power of data visualization! Go through this blog and discover why visualizations are crucial in Data Science and explore the most effective and game-changing types of visualizations that will revolutionize the way you interpret and extract insights from your data.

Data Visualization 368

Data Visualization Data Science Data Analysis Data Analysis 368

Analytics Vidhya

APRIL 6, 2022

Introduction Exploratory Data Analysis is a method of evaluating or comprehending data in order to derive insights or key characteristics. EDA can be divided into two categories: graphical analysis and non-graphical analysis. EDA is a critical component of any data science or machine learning process.

Exploratory Data Analysis 334

Exploratory Data Analysis EDA Data Analysis Data Analysis 334

insideBIGDATA

SEPTEMBER 5, 2023

In this column, we present a variety of short time-critical news items grouped by category such as M&A activity, people movements, funding news, financial results, industry alignments, customer wins, rumors and general scuttlebutt floating around the big data, data science and machine learning industries including behind-the-scenes anecdotes and (..)

Big Data 195

Big Data Big Data Machine Learning Machine Learning 195

insideBIGDATA

AUGUST 27, 2023

(NASDAQ: UPWK), the work marketplace and the preeminent destination for businesses to find trusted AI talent, released new platform data examining the skillset make up of talent and the search and hiring behaviors of companies in relation to Upwork’s fastest-growing category: Generative AI.

AI 195

AI AI Deep Learning Deep Learning 195

Analytics Vidhya

MAY 19, 2023

Statistics involves gathering and organizing raw data into an easily understandable format. This field of mathematics helps analyze data and apply the findings to address various data-related issues. There are two broad categories of statistical methods: descriptive and inferential statistics.

Analytics 238

Analytics Analytics Data Analysis Data Analysis 238

Analytics Vidhya

JULY 13, 2022

This article was published as a part of the Data Science Blogathon. Here there are two categories […]. Introduction In this article, we will see how to build an application that can recognize digits that are written by hand. The application will recognize our handwriting.

Data Science 365

Data Science Analytics Analytics Python 365

Analytics Vidhya

JULY 12, 2023

One often encounters datasets with categorical variables in data analysis and machine learning. By transforming category data into numerical labels, label encoding enables us to use them in various algorithms. […] The post How to Perform Label Encoding in Python? This is where label encoding comes into play.

Python 229

Python Machine Learning Machine Learning Data Analysis 229

insideBIGDATA

AUGUST 1, 2023

In this column, we present a variety of short time-critical news items grouped by category such as M&A activity, people movements, funding news, financial results, industry alignments, customer wins, rumors and general scuttlebutt floating around the big data, data science and machine learning industries including behind-the-scenes anecdotes and (..)

Big Data 195

Big Data Big Data Machine Learning Machine Learning 195

Analytics Vidhya

SEPTEMBER 9, 2020

In this article, we bust 11 common myths people have about data science. We have divided the myths into career, tools and role related categories. 11 Data Science Myths You Should Avoid at All Costs appeared first on Analytics Vidhya. The post Busted!

Data Science 400

Data Science Analytics Analytics 400

KDnuggets

FEBRUARY 24, 2023

This article will discuss SQL visualization, its role in augmenting the modern-day data engineer, and five categories of SQL visualization tools.

Data Engineering 224

Data Engineering Data Engineer Data Engineering Data Engineering 224

Analytics Vidhya

APRIL 15, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon. SUPERVISED LEARNING Before making you understand the broad category of. The post Understanding Supervised and Unsupervised Learning appeared first on Analytics Vidhya.

Supervised Learning 361

Supervised Learning Data Science Analytics Analytics 361

Analytics Vidhya

FEBRUARY 26, 2022

This article was published as a part of the Data Science Blogathon. Introduction Data Augmentation (DA) Technique is a process that enables us to artificially increase training data size by generating different versions of real datasets without actually collecting the data.

Natural Language Processing 291

Natural Language Processing Data Science Analytics Analytics 291

Analytics Vidhya

DECEMBER 21, 2021

This article was published as a part of the Data Science Blogathon Introduction Text classification is a machine-learning approach that groups text into pre-defined categories.

Natural Language Processing 380

Natural Language Processing Machine Learning Machine Learning Data Science 380

Data Science Dojo

FEBRUARY 2, 2024

An example illustrating rank-based encoding – Source: ResearchGate In the vast world of machine learning , getting your data ready is like laying the groundwork for success. This is particularly important for categorical features – data that is not in numbers.

Machine Learning 150

Machine Learning Machine Learning Algorithm 150

Data Science Dojo

MARCH 23, 2024

Their role is critical to ensure improved accuracy, faster training on data, and wider applicability. The very common model types under this category include encoder-only, decoder-only, and encoder-decoder transformers. It provides useful data insights, leading to the creation of effective strategies to enhance customer satisfaction.

Natural Language Processing 516

Natural Language Processing AI AI 516

Machine Learning Research at Apple

MARCH 28, 2024

Combining NNLMs for one or more of the categories could be one way to improve scalability. We examine three data sampling techniques and we experiment with adding adapter bottlenecks to the existing production NNLMs to model dialect-specific characteristics and investigate different strategies to train adapters.

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147

Analytics Vidhya

JUNE 19, 2022

This article was published as a part of the Data Science Blogathon. Azure provides different categories of cloud services such as infrastructure as a service (IaaS), platform as a service (PaaS), software as a service (SaaS), and serverless. Introduction on Microsoft Azure Microsoft Azure is a public cloud computing platform.

Azure 300

Azure Cloud Computing Data Science Analytics 300

FlowingData

MARCH 29, 2024

Alasdair Rae outlines the basics of visualizing basketball shot data with QGIS , an open-source software package typically used for geographic maps. Even if you’re not into basketball, sports data can be fun to poke at because it’s comprehensive and usually covers a good range of time and categories.

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Analytics Vidhya

OCTOBER 26, 2021

This article was published as a part of the Data Science Blogathon Introduction Quite often we have a requirement to visualize categorical data in a dataset. The post How To Build A Treemap In 3 Ways Using Python appeared first on Analytics Vidhya.

Python 277

Python Data Science Analytics Analytics 277

Analytics Vidhya

NOVEMBER 29, 2021

This article was published as a part of the Data Science Blogathon. Introduction Consider the following scenario: you are a product manager who wants to categorize customer feedback into two categories: favorable and unfavorable. The post Implementation of Gaussian Naive Bayes in Python Sklearn appeared first on Analytics Vidhya.

Python 300

Python Data Science Analytics Analytics 300

Dataconomy

DECEMBER 17, 2021

According to IDC, IoT data is forecasted to reach 73 zettabytes by 2025, while a recent study by Deloitte estimates that 40% of IoT devices will be capable of sharing location in 2025, up from 10% in 2020. This means time and space data is the fastest-growing big data category.

Big Data 238

Big Data Big Data Internet of Things Analytics 238

Analytics Vidhya

AUGUST 13, 2022

This article was published as a part of the Data Science Blogathon. The first task you do with each ticket is to classify it into one of the categories you […]. Introduction Suppose you are working in an IT firm as a support desk specialist and receive hundreds of support tickets you have to handle daily.

Data Science 234

Data Science Analytics Analytics Python 234

Towards AI

APRIL 8, 2024

Why are joint PMFs of multiple random variables important in data science? In Bayesian statistics, joint PMFs are crucial for computing posterior probabilities and updating the probability of hypotheses based on the observed data. What is a Joint Probability table? div(len(df)).unstack(fill_value=0)df_joint_pmf div(len(df)).unstack(fill_value=0)df_joint_pmf

Data Science 83

Data Science Machine Learning Machine Learning AI 83