KDnuggets

JUNE 1, 2022

The Complete Collection of Data Science Books - Part 2; Data Science Projects That Will Land You The Job in 2022; How to Become a Machine Learning Engineer; Dynamic Time Warping Algorithm in Time Series, Explained; Free Data Engineering Courses.

Data Science 209

Data Science Machine Learning Machine Learning Data Engineering 209

Analytics Vidhya

AUGUST 28, 2021

This article was published as a part of the Data Science Blogathon Overview: Machine Learning (ML) and data science applications are in high demand. When ML algorithms offer information before it is known, the benefits for business are significant. The ML algorithms, on […].

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ML ML Machine Learning Machine Learning 344

Data Science Dojo

OCTOBER 31, 2024

Research Data Scientist Description : Research Data Scientists are responsible for creating and testing experimental models and algorithms. With the continuous growth in AI, demand for remote data science jobs is set to rise. Familiarity with machine learning, algorithms, and statistical modeling.

Data Science 195

Data Science Data Scientist Machine Learning Machine Learning 195

ODSC - Open Data Science

NOVEMBER 28, 2024

A 2-for-1 ODSC East Black Friday Deal, Multi-Agent Systems, Financial Data Engineering, and LLM Evaluation ODSC East 2025 Black Friday Deal Take advantage of our 2-for-1 Black Friday sale and join the leading conference for data scientists and AI builders. Learn, innovate, and connect as we shape the future of AI — together!

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

Analytics Vidhya

JULY 5, 2022

This component develops large-scale data processing using scattered and compatible algorithms in the […]. Other components of Apache Hadoop include Hadoop Distributed File System (HDFS), Yarn, and Apache Pig. The post Learn Everything about MapReduce Architecture & its Components appeared first on Analytics Vidhya.

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Apache Hadoop Hadoop Data Science Algorithm 397

ODSC - Open Data Science

JANUARY 9, 2024

Now that we’re in 2024, it’s important to remember that data engineering is a critical discipline for any organization that wants to make the most of its data. These data professionals are responsible for building and maintaining the infrastructure that allows organizations to collect, store, process, and analyze data.

Data Engineering 97

Data Engineering Data Engineering Data Engineering Data Engineer 97

Analytics Vidhya

JANUARY 31, 2023

But are they still useful without the data? The machine learning algorithms heavily rely on data that we feed to them. The quality of data we feed to the algorithms […] The post Practicing Machine Learning with Imbalanced Dataset appeared first on Analytics Vidhya. The answer is No.

Machine Learning 319

Machine Learning Machine Learning Artificial Intelligence Artificial Intelligence 319

Data Science Dojo

MAY 10, 2023

Machine Learning Engineer Machine learning engineers are responsible for designing and building machine learning systems. They require strong programming skills, expertise in machine learning algorithms, and knowledge of data processing.

Data Science 366

Data Science Data Scientist Database Administration Machine Learning 366

Towards AI

MARCH 21, 2023

Navigating the World of Data Engineering: A Beginner’s Guide. A GLIMPSE OF DATA ENGINEERING ❤ IMAGE SOURCE: BY AUTHOR Data or data? No matter how you read or pronounce it, data always tells you a story directly or indirectly. Data engineering can be interpreted as learning the moral of the story.

Data Engineering 98

Data Engineering Data Engineering Data Engineering Data Engineer 98

Towards AI

OCTOBER 31, 2024

Here are three ways to use ChatGPT² to enhance data foundations: #1 Harmonize: Making data cleaner through AI A core challenge in analytics is maintaining data quality and integrity. Algorithms can automatically clean and preprocess data using techniques like outlier and anomaly detection.

Data Quality 122

Data Quality Analytics Analytics Clean Data 122

Analytics Vidhya

MAY 20, 2022

This article was published as a part of the Data Science Blogathon. Introduction In this article, we will be working withPySpark‘s MLIB library it is commonly known as the Machine learning library of PySpark where we can use any ML algorithm that was previously available in SkLearn (sci-kit-learn).

Machine Learning 329

Machine Learning Machine Learning Data Science ML 329

databricks

SEPTEMBER 21, 2023

Introduction In this blog post, we'll explore a set of advanced SQL functions available within Apache Spark that leverage the HyperLogLog algorithm, enabling.

SQL 276

SQL Algorithm Data Engineering Data Engineering 276

Analytics Vidhya

OCTOBER 1, 2021

This article was published as a part of the Data Science Blogathon Introduction to Machine Learning Before jumping to Supervised Machine Learning, let’s understand a bit about Machine Learning. The traditional algorithms need us to give a set of […].

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ML ML Machine Learning Machine Learning 306

Analytics Vidhya

MAY 17, 2023

By leveraging a machine learning algorithm and an importance-ranking metric, RFE evaluates each feature’s impact […] The post Recursive Feature Elimination: Working, Advantages & Examples appeared first on Analytics Vidhya.

Machine Learning 278

Machine Learning Machine Learning Algorithm Analytics 278

Analytics Vidhya

OCTOBER 8, 2022

Well-known websites like Facebook, LinkedIn, Instagram, Snapchat, Twitter, Amazon, Flipkart, and Netflix use different machine learning algorithms to draw people and increase their time spent on their websites […]. The post A Guide on Social Network Recommendation System appeared first on Analytics Vidhya.

Machine Learning 268

Machine Learning Machine Learning Data Science Algorithm 268

Analytics Vidhya

OCTOBER 12, 2022

This article was published as a part of the Data Science Blogathon. Introduction Standardization is one of the feature scaling techniques which scales down the data in such a way that the algorithms (like KNN, Logistic Regression, etc.)

Machine Learning 248

Machine Learning Machine Learning Data Science Algorithm 248

Pickl AI

APRIL 6, 2023

Accordingly, one of the most demanding roles is that of Azure Data Engineer Jobs that you might be interested in. The following blog will help you know about the Azure Data Engineering Job Description, salary, and certification course. How to Become an Azure Data Engineer?

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Azure Data Engineering Data Engineering Data Engineering 52

Data Science Dojo

APRIL 16, 2024

Integrating the knowledge of data science with engineering skills, they can design, build, and deploy machine learning (ML) models. Hence, their skillset is crucial to transform raw into algorithms that can make predictions, recognize patterns, and automate complex tasks.

AI 195

AI AI Machine Learning Machine Learning 195

Hacker News

NOVEMBER 19, 2024

Here are a few of the things that you might do as an AI Engineer at TigerEye: - Design, develop, and validate statistical models to explain past behavior and to predict future behavior of our customers’ sales teams - Own training, integration, deployment, versioning, and monitoring of ML components - Improve TigerEye’s existing metrics collection and (..)

Computer Science 153

Computer Science Computer Science ML ML 153

Data Science Dojo

FEBRUARY 13, 2025

Data + AI Summit Dates: June 912, 2025 Location: San Francisco, California In a world where data is king and AI is the game-changer, staying ahead means keeping up with the latest innovations in data science, ML, and analytics. Thats where Data + AI Summit 2025 comes in!

AI 250

AI AI Big Data Big Data 250

Data Science Dojo

FEBRUARY 20, 2023

Machine Learning is a set of techniques that allow computers to make predictions based on data without being programmed to do so. It uses algorithms to find patterns and make predictions based on the data, such as predicting what a user will click on. It also has ML algorithms built into the platform.

Machine Learning 195

Machine Learning Machine Learning AWS Azure 195

Data Science Dojo

JANUARY 10, 2023

All data roles are identical It’s a common data science myth that all data roles are the same. So, let’s distinguish between some common data roles – data engineer, data scientist, and data analyst. So, what makes a good data science profile?

Data Science 195

Data Science Data Scientist Data Analyst Machine Learning 195

phData

SEPTEMBER 29, 2023

When you think of data engineering , what comes to mind? In reality, though, if you use data (read: any information), you are most likely practicing some form of data engineering every single day. Said differently, any tools or steps we use to help us utilize data can be considered data engineering.

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

Towards AI

JULY 1, 2024

Learn the basics of data engineering to improve your ML modelsPhoto by Mike Benna on Unsplash It is not news that developing Machine Learning algorithms requires data, often a lot of data. Collecting this data is not trivial, in fact, it is one of the most relevant and difficult parts of the entire workflow.

ETL 99

ETL Data Scientist Data Engineering Data Engineering 99

Data Science Dojo

JULY 7, 2023

Data Science intertwines statistics, problem-solving, and programming to extract valuable insights from vast data sets. This discipline takes raw data, deciphers it, and turns it into a digestible format using various tools and algorithms. Tools such as Python, R, and SQL help to manipulate and analyze data.

Data Science 195

Data Science Data Scientist Python Decision Trees 195

Pickl AI

JULY 25, 2023

Unfolding the difference between data engineer, data scientist, and data analyst. Data engineers are essential professionals responsible for designing, constructing, and maintaining an organization’s data infrastructure. Read more to know.

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

DataSeries

AUGUST 15, 2024

Enrich data engineering skills by building problem-solving ability with real-world projects, teaming with peers, participating in coding challenges, and more. Globally several organizations are hiring data engineers to extract, process and analyze information, which is available in the vast volumes of data sets.

Data Engineering 40

Data Engineering Data Engineering Data Engineering Data Engineer 40

ODSC - Open Data Science

FEBRUARY 15, 2024

We couldn’t be more excited to announce the first sessions for our second annual Data Engineering Summit , co-located with ODSC East this April. Join us for 2 days of talks and panels from leading experts and data engineering pioneers. Is Gen AI A Data Engineering or Software Engineering Problem?

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

ODSC - Open Data Science

MAY 5, 2023

Data science and data engineering are incredibly resource intensive. Between accessing databases, using frameworks, using applications, and more, a lot of power is needed to run even the simplest algorithms. As such, here are a few data engineering and data science cloud options to make your life easier.

Data Science 52

Data Science Data Engineering Data Engineering Data Engineering 52

Smart Data Collective

NOVEMBER 8, 2020

This explains the current surge in demand for data engineers, especially in data-driven companies. That said, if you are determined to be a data engineer , getting to know about big data and careers in big data comes in handy. Similarly, various tools used in data engineering revolve around Scala.

Data Engineering 104

Data Engineering Data Engineering Data Engineering Data Engineer 104

Pickl AI

DECEMBER 25, 2024

Key Tools and Techniques Data Science relies on a wide array of tools and techniques to process and analyze large datasets. Programming languages like Python and R are commonly used for data manipulation, visualization, and statistical modeling. Data Science, however, uses predictive and prescriptive solutions.

Data Science 52

Data Science Analytics Analytics Data Scientist 52

IBM Data Science in Practice

JANUARY 4, 2023

Alternatively, Match 360 provides a default algorithm to assist the matching process. This algorithm weighs the attributes and determines the difference of two records. The algorithm decides how much a difference of two records affects the decision to consider the records to belong to the same entity or not.

Algorithm 130

Algorithm Database Data Quality Data Engineer 130

Smart Data Collective

JUNE 10, 2022

The Bureau of Labor Statistics reports that there are over 105,000 data scientists in the United States. The average data scientist earns over $108,000 a year. You would need to have the skills to analyze large amounts of complex data and find patterns that would benefit the business or organization you work for. Data Engineer.

Data Science 144

Data Science Data Scientist Machine Learning Machine Learning 144

ODSC - Open Data Science

JANUARY 4, 2024

Trending Data Engineering Topics, the Top AI News from 2023, and Mapping Out the Top Open-Source LLM Frameworks 10 Data Engineering Topics and Trends You Need to Know in 2024 Let’s dive in and explore 10 data engineering trends that are expected to shape the industry in 2024 and beyond.

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

Data Science Dojo

APRIL 27, 2023

This blog lists down-trending data science, analytics, and engineering GitHub repositories that can help you with learning data science to build your own portfolio.  What is GitHub? GitHub is a powerful platform for data scientists, data analysts, data engineers, Python and R developers, and more.

Data Science 195

Data Science Analytics Analytics Power BI 195

ODSC - Open Data Science

FEBRUARY 2, 2023

Just as a writer needs to know core skills like sentence structure, grammar, and so on, data scientists at all levels should know core data science skills like programming, computer science, algorithms, and so on. This will lead to algorithm development for any machine or deep learning processes.

Data Science 98

Data Science Data Scientist Computer Science Computer Science 98

Towards AI

NOVEMBER 8, 2024

Table: Research Phase vs Production Phase Datasets The contrast highlights the “production data” we’ll call “data” in this post. Data is a key differentiator in ML projects (more on this in my blog post below). We don’t have better algorithms; we just have more data.

ML 111

ML ML Data Preparation Data Engineer 111