ODSC - Open Data Science

MARCH 30, 2023

Using Azure ML to Train a Serengeti Data Model, Fast Option Pricing with DL, and How To Connect a GPU to a Container Using Azure ML to Train a Serengeti Data Model for Animal Identification In this article, we will cover how you can train a model using Notebooks in Azure Machine Learning Studio.

Azure 52

Azure ML ML Data Modeling 52

Mlearning.ai

MARCH 3, 2023

Data Engineering A data engineers start to simplification Introduction A lot of time folks start directly jumping into KPIs ( Key Performace Indicators) without understanding the need for those KPIs. I have met with clients who have dumped all the data they had and never figured out what they really wanted to achieve.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

IBM Journey to AI blog

SEPTEMBER 19, 2023

Overview: Data science vs data analytics Think of data science as the overarching umbrella that covers a wide range of tasks performed to find patterns in large datasets, structure data for use, train machine learning models and develop artificial intelligence (AI) applications.

Data Science 84

Data Science Analytics Analytics Data Scientist 84

Smart Data Collective

MAY 29, 2023

Three Different Analysts Data analysis as a whole is a very broad concept which can and should be broken down into three separate, more specific categories : Data Scientist, Data Engineer, and Data Analyst. Data Scientist These employees are programmers and analysts combined.

Data Analyst 78

Data Analyst SQL Data Scientist Data Analysis 78

Dataconomy

MAY 2, 2023

What do machine learning engineers do: They implement and train machine learning models Data modeling One of the primary tasks in machine learning is to analyze unstructured data models, which requires a solid foundation in data modeling. How data engineers tame Big Data?

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ML ML Machine Learning Machine Learning 110

Pickl AI

MARCH 22, 2023

The USP of the company focuses on marketing analytics, business and retail analytics, Artificial Intelligence, Marketing Mix Modelling, Customer Analytics and Pricing Analytics. With more than 200 Data Scientists associated with the company, Cartesian Consulting follows an impact-oriented approach. Lakhs annually.

Data Science 52

Data Science Data Scientist Analytics Analytics 52

ODSC - Open Data Science

APRIL 26, 2023

Though just about every industry imaginable utilizes the skills of a data-focused professional, each has its own challenges, needs, and desired outcomes. This is why you’ll often find that there are jobs in AI specific to an industry, or desired outcome when it comes to data.

Data Analyst 52

Data Analyst Machine Learning Machine Learning Power BI 52

Pickl AI

JANUARY 16, 2024

Predictive Modeler Harnessing the power of algorithms to forecast future trends, aiding businesses in strategic decision-making. Cybersecurity Analyst Safeguarding organisations by analysing data to identify and prevent cyber threats, ensuring the security and integrity of digital systems.

Data Analyst 52

Data Analyst Data Analysis Data Analysis Analytics 52

Alation

SEPTEMBER 7, 2021

In the previous blog , we discussed how Alation provides a platform for data scientists and analysts to complete projects and analysis at speed. In this blog we will discuss how Alation helps minimize risk with active data governance. But governance is a time-consuming process (for users and data stewards alike).

Data Governance 59

Data Governance Data Scientist Data Quality Data Profiling 59

IBM Journey to AI blog

JULY 6, 2023

It uses advanced tools to look at raw data, gather a data set, process it, and develop insights to create meaning. Areas making up the data science field include mining, statistics, data analytics, data modeling, machine learning modeling and programming.

Machine Learning 60

Machine Learning Machine Learning Data Science Big Data 60

Mlearning.ai

MAY 16, 2023

Data engineering is a rapidly growing field that designs and develops systems that process and manage large amounts of data. There are various architectural design patterns in data engineering that are used to solve different data-related problems.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

Iguazio

DECEMBER 14, 2023

Who This Book Is For This book is for practitioners in charge of building, managing, maintaining, and operationalizing the ML process end to end: Data science / AI / ML leaders: Heads of Data Science, VPs of Advanced Analytics, AI Lead etc. Monitor the data, models, and applications to guarantee their availability and performance.

ML 52

ML ML Data Science Data Preparation 52

AWS Machine Learning Blog

JANUARY 5, 2024

Collaboration – Data scientists each worked on their own local Jupyter notebooks to create and train ML models. They lacked an effective method for sharing and collaborating with other data scientists. This has helped the data scientist team to create and test pipelines at a much faster pace.

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ODSC - Open Data Science

OCTOBER 15, 2023

Elementl / Dagster Labs Elementl and Dagster Labs are both companies that provide platforms for building and managing data pipelines. Elementl’s platform is designed for data engineers, while Dagster Labs’ platform is designed for data scientists. ArangoDB is designed to be scalable, reliable, and easy to use.

Machine Learning 52

Machine Learning Machine Learning Data Pipeline AI 52

Pickl AI

APRIL 10, 2023

They must be capable of comprehending intricate data structures and have a solid grasp of SQL queries. Database creation and maintenance: SQL data analysts are responsible for creating and keeping up-to-date secure databases.

Data Analyst 52

Data Analyst SQL Data Analysis Data Analysis 52

Mlearning.ai

FEBRUARY 16, 2023

Therefore, you’ll be empowered to truncate and reprocess data if bugs are detected and provide an excellent raw data source for data scientists. Use Multiple Data Models With on-premise data warehouses, storing multiple copies of data can be too expensive. What will You Attain with Snowflake?

Data Warehouse 52

Data Warehouse Business Intelligence Business Intelligence Database 52

The MLOps Blog

OCTOBER 3, 2023

So I tell people honestly, I’ve spent the last eight years working up and down the data and ML value chain effectively – a fancy way of saying “job hopping.” How to transition from data analytics to MLOps engineering Piotr: Miki, you’ve been a data scientist, right? And later, an MLOps engineer.

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ML ML Data Scientist Machine Learning 52

Data Science Blog

SEPTEMBER 19, 2023

Streamlined Collaboration Among Teams Data Warehouse Systems in the cloud often involve cross-functional teams — data engineers, data scientists, and system administrators. This ensures that the data models and queries developed by data professionals are consistent with the underlying infrastructure.

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Data Warehouse Azure SQL Database 259

AWS Machine Learning Blog

OCTOBER 20, 2023

Data scientists from ML teams across different business units federate into their team’s development environment to build the model pipeline. Data scientists search and pull features from the central feature store catalog, build models through experiments, and select the best model for promotion.

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ML ML AWS Data Lakes 103

Alation

JULY 19, 2022

These days, data scientists are in high demand. Across the country, data scientists have an unemployment rate of 2% and command an average salary of nearly $100,000. For these reasons, finding and evaluating data is often time-consuming. Get the data. Explore the data. Model the data.

Data Scientist 59

Data Scientist Data Quality Data Analyst Data Science 59

Snorkel AI

MAY 12, 2023

My name is Erin Babinski and I’m a data scientist at Capital One, and I’m speaking today with my colleagues Bayan and Kishore. We’re here to talk to you all about data-centric AI. Publishing standards for data and governance of that data is either missing or very widely far from an ideal.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

Snorkel AI

MAY 12, 2023

My name is Erin Babinski and I’m a data scientist at Capital One, and I’m speaking today with my colleagues Bayan and Kishore. We’re here to talk to you all about data-centric AI. Publishing standards for data and governance of that data is either missing or very widely far from an ideal.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

Pickl AI

DECEMBER 4, 2023

. ₹ 6,20000 Analytical skills, proficiency in Data Analysis tools (e.g., Data Scientist Involves advanced analysis of complex datasets to extract insights and create predictive models. Data Engineer Builds and manages the infrastructure for collecting, storing, and analysing large volumes of data.

Data Analysis 52

Data Analysis Data Analysis Artificial Intelligence Artificial Intelligence 52

ODSC - Open Data Science

MAY 10, 2023

Data-centric AI, in his opinion, is based on the following principles: It’s time to focus on the data — after all the progress achieved in algorithms means it’s now time to spend more time on the data Inconsistent data labels are common since reasonable, well-trained people can see things differently. The choice is yours.

Data Scientist 87

Data Scientist Data Science Deep Learning Deep Learning 87

DagsHub

DECEMBER 14, 2023

Why Version Control is Essential in ML Version control is an indispensable practice in machine learning (ML) for several crucial reasons: Reproducibility: ML projects are often iterative and involve numerous experiments with different data, models, and hyperparameters.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

Iguazio

FEBRUARY 8, 2024

Data engineers, data scientists and other data professional leaders have been racing to implement gen AI into their engineering efforts. Data Pipeline - Manages and processes various data sources. Application Pipeline - Manages requests and data/model validations. What is MLOps?

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ML ML AI AI 52

The MLOps Blog

JUNE 27, 2023

Alignment to other tools in the organization’s tech stack Consider how well the MLOps tool integrates with your existing tools and workflows, such as data sources, data engineering platforms, code repositories, CI/CD pipelines, monitoring systems, etc. For example, neptune.ai Check out the Kubeflow documentation.

Machine Learning 134

Machine Learning Machine Learning ML ML 134

Pickl AI

AUGUST 23, 2023

Predictive Analytics One of the most remarkable aspects of Data Science in stock market analysis is its predictive capabilities. Through sophisticated algorithms and Machine Learning models , data scientists can predict stock price movements with a degree of accuracy that was previously unthinkable.

Data Science 52

Data Science Machine Learning Machine Learning Algorithm 52

Alation

OCTOBER 27, 2022

Like so many data teams out there, we need to maximize our throughput whilst ensuring quality. Jason: I’m curious to learn about your modern data stack. Adrian Lievano, Senior Data Scientist, Alation : Most of our data sources are connected and extracted using Fivetran , and then transported to raw storage in Snowflake.

Data Analyst 52

Data Analyst Data Scientist Data Warehouse Analytics 52

Alation

AUGUST 16, 2022

But do they empower many user types to quickly find trusted data for a business decision or data model? Many data catalogs suffer from a lack of adoption because they are too technical. These include data analysts, stewards, business users , and data engineers. Functionality and Range of Services.

Data Quality 52

Data Quality Data Governance Cloud Data Data Engineering 52

Tableau

SEPTEMBER 23, 2021

At Tableau, we wanted to understand use cases and common issues from our most advanced data scientists to general data consumers. While not exhaustive, here are additional capabilities to consider as part of your data management and governance solution: Data preparation. Data modeling.

Data Governance 91

Data Governance Analytics Analytics Tableau 91

Tableau

SEPTEMBER 23, 2021

At Tableau, we wanted to understand use cases and common issues from our most advanced data scientists to general data consumers. While not exhaustive, here are additional capabilities to consider as part of your data management and governance solution: Data preparation. Data modeling.

Data Governance 79

Data Governance Analytics Analytics Tableau 79

The MLOps Blog

DECEMBER 28, 2022

Data scientists frame the business problem and the objective into a statistical solution and start with the very first step of data exploration. Team composition The team comprises domain experts, data engineers, data scientists, and ML engineers.

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ML ML Data Scientist Machine Learning 78

DataRobot

NOVEMBER 12, 2021

Of the organizations surveyed, 52 percent were seeking machine learning modelers and data scientists, 49 percent needed employees with a better understanding of business use cases, and 42 percent lacked people with data engineering skills. Your team already understands your business and your data.

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AI AI Data Scientist Machine Learning 98

DataRobot

FEBRUARY 22, 2021

The founding of the 10X Academy is part of DataRobot’s commitment to developing automation that improves the productivity of data scientists while democratizing access to AI for non-data scientists.

Data Science 52

Data Science Citizen Data Scientist Data Scientist Data Analyst 52

phData

JULY 18, 2023

Enter dbt dbt provides SQL-centric transformations for your data modeling and transformations, which is efficient for scrubbing and transforming your data while being an easy skill set to hire for and develop within your teams. Testing: Data engineering should be treated as a form of software engineering.

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Data Warehouse SQL Cloud Data Analytics 52