Data Science Blog

JUNE 30, 2023

The data is obtained from the Internet via APIs and web scraping, and the job titles and the skills listed in them are identified and extracted from them using Natural Language Processing (NLP) or more specific from Named-Entity Recognition (NER). Over the time, it will provides you the answer on your questions related to which tool to learn!

Data Engineer 130

Data Engineer Data Engineering Data Engineering Data Engineering 130

KDnuggets

NOVEMBER 30, 2022

What is Chebychev's Theorem and How Does it Apply to Data Science? Linux for Data Science Cheatsheet • The Complete Data Engineering Study Roadmap • 10 Amazing Machine Learning Visualizations You Should Know in 2023 • 7 SQL Concepts Needed for Data Science.

Data Science 145

Data Science SQL Machine Learning Machine Learning 145

ODSC - Open Data Science

MARCH 6, 2023

In an effort to learn more about our community, we recently shared a survey about machine learning topics, including what platforms you’re using, in what industries, and what problems you’re facing. For currently-used machine learning frameworks, some of the usual contenders were popular as expected.

Machine Learning 116

Machine Learning Machine Learning Data Science Deep Learning 116

Data Science Dojo

MAY 10, 2023

Data Scientist Data scientists are responsible for designing and implementing data models, analyzing and interpreting data, and communicating insights to stakeholders. They require strong programming skills, knowledge of statistical analysis, and expertise in machine learning.

Data Science 253

Data Science Data Scientist Database Administration Machine Learning 253

Analytics Vidhya

SEPTEMBER 30, 2021

This article was published as a part of the Data Science Blogathon Overview Databricks in simple terms is a data warehousing, machine learning web-based platform developed by the creators of Spark. But Databricks is much more than that.

Machine Learning 353

Machine Learning Machine Learning Data Science Analytics 353

Data Science Dojo

OCTOBER 31, 2024

Research Data Scientist Description : Research Data Scientists are responsible for creating and testing experimental models and algorithms. Key Skills: Mastery in machine learning frameworks like PyTorch or TensorFlow is essential, along with a solid foundation in unsupervised learning methods.

Data Science 195

Data Science Data Scientist Machine Learning Machine Learning 195

Smart Data Collective

OCTOBER 11, 2021

If you enjoy working with data, or if you’re just interested in a career with a lot of potential upward trajectory, you might consider a career as a data engineer. But what exactly does a data engineer do, and how can you begin your career in this niche? What Is a Data Engineer?

Data Engineer 119

Data Engineer Data Engineering Data Engineering Data Engineering 119

KDnuggets

OCTOBER 30, 2019

Also: Highest paid positions in 2019 are DevOps, Data Scientist, Data Engineer (all over $100K) - Stack Overflow Salary Calculator, Updated; A neural net solves the three-body problem 100 million times faster; The Last SQL Guide for Data Analysis You’ll Ever Need; How YouTube is Recommending Your Next Video.

Machine Learning 114

Machine Learning Machine Learning Data Scientist SQL 114

ODSC - Open Data Science

MARCH 13, 2023

Recently, we posted the first article recapping our recent machine learning survey. There, we talked about some of the results, such as what programming languages machine learning practitioners use, what frameworks they use, and what areas of the field they’re interested in. As the chart shows, two major themes emerged.

Machine Learning 94

Machine Learning Machine Learning Data Wrangling Data Science 94

AWS Machine Learning Blog

AUGUST 8, 2024

As one of the largest AWS customers, Twilio engages with data, artificial intelligence (AI), and machine learning (ML) services to run their daily workloads. Data is the foundational layer for all generative AI and ML applications. The following diagram illustrates the solution architecture.

SQL 106

SQL Data Lakes Data Analyst AWS 106

Data Science Dojo

MAY 18, 2023

In this panel, we will discuss how MLOps can help overcome challenges in operationalizing machine learning models, such as version control, deployment, and monitoring. Additionally, how ML Ops is particularly helpful for large-scale systems like ad auctions, where high data volume and velocity can pose unique challenges.

Data Science 195

Data Science AI AI SQL 195

AWS Machine Learning Blog

JUNE 20, 2024

The data is stored in a data lake and retrieved by SQL using Amazon Athena. The following figure shows a search query that was translated to SQL and run. Data is normally stored in databases, and can be queried using the most common query language, SQL. The challenge is to assure quality.

SQL 94

SQL Database AWS Machine Learning 94

KDnuggets

NOVEMBER 6, 2023

If you know SQL, you can easily learn Cypher and open up a huge opportunity for data analysis. Graph databases are quickly becoming a core part of the analytics toolset for enterprise IT organizations.

Database 265

Database SQL Data Analysis Data Analysis 265

KDnuggets

DECEMBER 15, 2022

What is Chebychev's Theorem and How Does it Apply to Data Science? • Git for Data Science Cheatsheet • 7 SQL Concepts Needed for Data Science • The Complete Data Engineering Study Roadmap •.

Data Science 110

Data Science SQL Machine Learning Machine Learning 110

AWS Machine Learning Blog

OCTOBER 24, 2024

Machine learning (ML) helps organizations to increase revenue, drive business growth, and reduce costs by optimizing core business functions such as supply and demand forecasting, customer churn prediction, credit risk scoring, pricing, predicting late shipments, and many others. Basic knowledge of a SQL query editor.

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Data Warehouse Machine Learning Machine Learning Cloud Data 97

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? What is machine learning?

Machine Learning 70

Machine Learning Machine Learning Data Science Big Data 70

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

Dataconomy

JULY 24, 2023

Coding skills are essential for tasks such as data cleaning, analysis, visualization, and implementing machine learning algorithms. You might be asking, “How to become a data scientist with a background in a different field?” Machine learning Machine learning is a key part of data science.

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Data Scientist Data Science Data Analyst Machine Learning 172

Flipboard

JUNE 22, 2023

Data engineering startup Prophecy is giving a new turn to data pipeline creation. Known for its low-code SQL tooling, the California-based company today announced data copilot, a generative AI assistant that can create trusted data pipelines from natural language prompts and improve pipeline quality …

Data Pipeline 123

Data Pipeline SQL Data Engineering Data Engineer 123

Data Science 101

FEBRUARY 15, 2020

Azure Cognitive Services Named Entity Recognition gets some new types Persontype, product, event, organization, date are just some of them Amazon Aurora PostgreSQL Supports Machine Learning Aurora PostgreSQL can now use SQL to call ML models created with SageMaker. Google Announces BigQuery Data Challenge.

Cloud Data 112

Cloud Data Data Science Deep Learning Deep Learning 112

Data Science Dojo

JULY 3, 2024

Data science bootcamps are intensive short-term educational programs designed to equip individuals with the skills needed to enter or advance in the field of data science. They cover a wide range of topics, ranging from Python, R, and statistics to machine learning and data visualization.

Data Science 150

Data Science Machine Learning Machine Learning Data Visualization 150

Flipboard

DECEMBER 11, 2024

Organizations are building data-driven applications to guide business decisions, improve agility, and drive innovation. Many of these applications are complex to build because they require collaboration across teams and the integration of data, tools, and services.

SQL 160

SQL AWS Data Lakes AI 160

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

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 Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

Towards AI

FEBRUARY 11, 2024

Solution Steps Before solving any SQL Problem, it is important to understand the schema of a table, relationships, and data types used in the table. That is the best feature of SQL: there is no limit to solving a problem in a particular way. Click Here to see the problem statement from Data Lemur. All the best.

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SQL AI AI Data Engineer 105

AWS Machine Learning Blog

JUNE 6, 2023

Amazon SageMaker Feature Store is a purpose-built service to store and retrieve feature data for use by machine learning (ML) models. Feature Store provides an online store capable of low-latency, high-throughput reads and writes, and an offline store that provides bulk access to all historical record data.

Machine Learning 79

Machine Learning Machine Learning Python SQL 79

Pickl AI

NOVEMBER 4, 2024

Summary: The fundamentals of Data Engineering encompass essential practices like data modelling, warehousing, pipelines, and integration. Understanding these concepts enables professionals to build robust systems that facilitate effective data management and insightful analysis. What is Data Engineering?

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

Applied Data Science

AUGUST 2, 2021

Machine learning The 6 key trends you need to know in 2021 ? With a range of role types available, how do you find the perfect balance of Data Scientists , Data Engineers and Data Analysts to include in your team? The Data Engineer Not everyone working on a data science project is a data scientist.

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Data Science Data Scientist ML ML 130

AWS Machine Learning Blog

DECEMBER 1, 2023

The ability to quickly build and deploy machine learning (ML) models is becoming increasingly important in today’s data-driven world. From data collection and cleaning to feature engineering, model building, tuning, and deployment, ML projects often take months for developers to complete.

Machine Learning 96

Machine Learning Machine Learning Data Preparation ML 96

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. While knowing Python, R, and SQL are expected, you’ll need to go beyond that.

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Data Science Data Scientist Computer Science Computer Science 98

ODSC - Open Data Science

JANUARY 18, 2024

Data engineering is a rapidly growing field, and there is a high demand for skilled data engineers. If you are a data scientist, you may be wondering if you can transition into data engineering. In this blog post, we will discuss how you can become a data engineer if you are a data scientist.

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

Pickl AI

APRIL 19, 2023

Machine Learning is the part of Artificial Intelligence and computer science that emphasizes on the use of data and algorithms, imitating the way humans learn and improving accuracy. Machine Learning is becoming increasingly popular and crucial in today’s market for effective productivity and decision-making processes.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

Data Science Blog

NOVEMBER 15, 2023

Simple Data Model for a Process Mining Event Log As part of data engineering, the data traces that indicate process activities are brought into a log-like schema. A simple event log is therefore a simple table with the minimum requirement of a process number (case ID), a time stamp and an activity description.

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Data Modeling Data Models Business Intelligence Business Intelligence 245

The MLOps Blog

SEPTEMBER 7, 2023

Best practices for building ETLs for ML Best practices for building ETLs for ML | Source: Author The significance of ETLs in machine learning projects Exploring a pivotal facet of every machine learning endeavor: ETLs. These insights are specifically curated for machine learning applications.

Machine Learning 52

Machine Learning Machine Learning ETL ML 52

Pickl AI

AUGUST 1, 2023

Aspiring and experienced Data Engineers alike can benefit from a curated list of books covering essential concepts and practical techniques. These 10 Best Data Engineering Books for beginners encompass a range of topics, from foundational principles to advanced data processing methods. What is Data Engineering?

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

Data Science Blog

SEPTEMBER 3, 2024

Während vor zehn Jahren ich für Celonis noch eine Installation erst einer MS SQL Server Datenbank, etwas später dann bevorzugt eine SAP Hana Datenbank auf einem on-prem Server beim Kunden voraussetzend installieren musste, bevor ich dann zur Installation der Celonis ServerAnwendung selbst kam, ist es heute eine 100% externe Cloud-Lösung.

Data Science 130

Data Science Power BI Azure Data Warehouse 130

AWS Machine Learning Blog

JUNE 5, 2023

Data is the foundation for machine learning (ML) algorithms. One of the most common formats for storing large amounts of data is Apache Parquet due to its compact and highly efficient format. Athena allows applications to use standard SQL to query massive amounts of data on an S3 data lake.

Machine Learning 73

Machine Learning Machine Learning AWS Data Lakes 73