ODSC - Open Data Science

JANUARY 25, 2023

The Azure ML team has long focused on bringing you a resilient product, and its latest features take one giant leap in that direction, as illustrated in the graph below (Figure 1). Continue reading to learn more about Azure ML’s latest announcements. This is the motivation behind several of Azure ML’s latest features.

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ODSC - Open Data Science

APRIL 18, 2023

Mini-Bootcamp and VIP Pass holders will have access to four live virtual sessions on data science fundamentals. Confirmed sessions include: An Introduction to Data Wrangling with SQL with Sheamus McGovern, Software Architect, Data Engineer, and AI expert Programming with Data: Python and Pandas with Daniel Gerlanc, Sr.

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ODSC - Open Data Science

DECEMBER 7, 2023

ML Pros Deep-Dive into Machine Learning Techniques and MLOps Seth Juarez | Principal Program Manager, AI Platform | Microsoft Learn how new, innovative features in Azure machine learning can help you collaborate and streamline the management of thousands of models across teams. Check out a few of the highlights from each group below.

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Pickl AI

NOVEMBER 4, 2024

Its robust ecosystem of libraries and frameworks tailored for Data Science, such as NumPy, Pandas, and Scikit-learn, contributes significantly to its popularity. Moreover, Python’s straightforward syntax allows Data Scientists to focus on problem-solving rather than grappling with complex code.

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ODSC - Open Data Science

FEBRUARY 20, 2023

We’ll also have a series of introductory sessions on AI literacy, intros to programming, etc.

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ODSC - Open Data Science

AUGUST 15, 2023

To help you stay ahead of the curve, ODSC APAC this August 22nd-23rd will feature expert-led training sessions in both data science fundamentals and cutting-edge tools and frameworks. Check out a few of them below.

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Towards AI

JUNE 27, 2023

This article is part of the AWS SageMaker series for exploration of ’31 Questions that Shape Fortune 500 ML Strategy’. Automation] How can the transformation steps be applied in real-time to the live data before inference?▢ Collaboration] How can a data scientist share and discover the engineered features to avoid effort duplication?▢

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ODSC - Open Data Science

MARCH 2, 2023

Being able to interpret, communicate, and make informed decisions about the data you have will make or break you as a data scientist. Finally, data literacy is a key component of data ethics, which ensures that data is used in a responsible and ethical manner. Conclusion This all sounds great, right?

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Pickl AI

MAY 31, 2023

Machine Learning: Data Science aspirants need to have a good and concise understanding on Machine Learning algorithms including both supervised and unsupervised learning. Proficiency in ML is understood when these are not just present in the aspirant in conceptual ways but also in terms of its applications in solving business problems.

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Becoming Human

MAY 15, 2023

Note : Now, Start joining Data Science communities on social media platforms. These communities will help you to be updated in the field, because there are some experienced data scientists posting the stuff, or you can talk with them so they will also guide you in your journey.

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ODSC - Open Data Science

APRIL 3, 2023

Skills like effective verbal and written communication will help back up the numbers, while data visualization (specific frameworks in the next section) can help you tell a complete story. Data Wrangling: Data Quality, ETL, Databases, Big Data The modern data analyst is expected to be able to source and retrieve their own data for analysis.

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phData

FEBRUARY 14, 2023

To keep up with the rapidly growing Insurance industry and its increasing data and compute needs, it’s important to centralize data from multiple sources while maintaining high performance and concurrency. Also today’s volume, variety, and velocity of data, only intensify the data-sharing issues.

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ODSC - Open Data Science

JANUARY 28, 2025

While traditional roles like data scientists and machine learning engineers remain essential, new positions like large language model (LLM) engineers and prompt engineers have gained traction. The Evolution of AI JobRoles McGovern provided a deep dive into the evolving AI job market , identifying shifts in demand for specific roles.

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Mlearning.ai

JULY 9, 2023

Empowering Data Scientists and Engineers with Lightning-Fast Data Analysis and Transformation Capabilities Photo by Hans-Jurgen Mager on Unsplash ?Goal Abstract Polars is a fast-growing open-source data frame library that is rapidly becoming the preferred choice for data scientists and data engineers in Python.

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The MLOps Blog

OCTOBER 20, 2023

Nevertheless, many data scientists will agree that they can be really valuable – if used well. And that’s what we’re going to focus on in this article, which is the second in my series on Software Patterns for Data Science & ML Engineering. Data on its own is not sufficient for a cohesive story. documentation.

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IBM Journey to AI blog

DECEMBER 16, 2022

Let’s look at five benefits of an enterprise data catalog and how they make Alex’s workflow more efficient and her data-driven analysis more informed and relevant. A data catalog replaces tedious request and data-wrangling processes with a fast and seamless user experience to manage and access data products.

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Snorkel AI

APRIL 13, 2023

The natural language interface enables a wide audience of both ML and non-ML experts to engage with the models. A next huge challenge is data preparation, or data wrangling tasks, such as identifying and filling in missing values or detecting data entry errors and databases. But again, there are challenges.

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Snorkel AI

APRIL 13, 2023

The natural language interface enables a wide audience of both ML and non-ML experts to engage with the models. A next huge challenge is data preparation, or data wrangling tasks, such as identifying and filling in missing values or detecting data entry errors and databases. But again, there are challenges.

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Heartbeat

DECEMBER 27, 2023

The machine learning (ML) lifecycle defines steps to derive values to meet business objectives using ML and artificial intelligence (AI). Here are some details about these packages: jupyterlab is for model building and data exploration. matplotlib is for data visualization. Why Use Docker for Machine Learning? Flask==2.1.2

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phData

NOVEMBER 4, 2024

By providing an integrated environment for data preparation, machine learning, and collaborative analytics, Dataiku empowers teams to harness the full potential of their data without requiring extensive technical expertise. The platform allows data scientists, analysts, and business stakeholders to work together seamlessly.

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Pickl AI

MAY 15, 2024

This guide unlocks the path from Data Analyst to Data Scientist Architect. Data Analyst to Data Scientist: Level-up Your Data Science Career The ever-evolving field of Data Science is witnessing an explosion of data volume and complexity.

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ODSC - Open Data Science

SEPTEMBER 20, 2023

Monday’s sessions will cover a wide range of topics, from Generative AI and LLMs to MLOps and Data Visualization. Register now while tickets are 50% off. Prices go up Friday!

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AWS Machine Learning Blog

MARCH 27, 2025

When implementing machine learning (ML) workflows in Amazon SageMaker Canvas , organizations might need to consider external dependencies required for their specific use cases. Without writing a single line of code, users can explore datasets, transform data, build models, and generate predictions.

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ODSC - Open Data Science

MARCH 18, 2025

Allen Downey, PhD, Principal Data Scientist at PyMCLabs Allen is the author of several booksincluding Think Python, Think Bayes, and Probably Overthinking Itand a blog about data science and Bayesian statistics. This years event is no different, and heres a rundown of 15 fan-favorite speakers who are returning onceagain.

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