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To DataScience Enthusiasts, We are happy to bring you another webinar into ‘The DataHour’ series. The webinar is based on building and operationalizing your ML Model using Tableau Business Science.
Introduction With regard to educating its community about datascience, Analytics Vidhya has long been at the forefront. We periodically hold “DataHour” events to increase community interest in studying datascience. The post Introduction to BigQuery ML appeared first on Analytics Vidhya.
At Analytics Vidhya, the community has been at the forefront since its inception with aim of building the best AI ML ecosystem […]. The post Introducing The DataHour Series – Webinars with Industry Leaders appeared first on Analytics Vidhya. Well.guess what?
This technical webinar on Aug 14 discusses traditional and modern approaches for interpreting black box models. Additionally, we will review cutting edge research coming out of UCSF, CMU, and industry.
To get you started, DataScience Dojo and Weaviate have teamed up to bring you an exciting webinar series: Master Vector Embeddings with Weaviate. We have carefully curated the series to empower AI enthusiasts, data scientists, and industry professionals with a deep understanding of vector embeddings.
Summary: Python for DataScience is crucial for efficiently analysing large datasets. Introduction Python for DataScience has emerged as a pivotal tool in the data-driven world. Key Takeaways Python’s simplicity makes it ideal for Data Analysis. in 2022, according to the PYPL Index.
Introduction DataScience is the emerging and essential domain of the current time, especially in India and Analytics Vidhya is India’s largest Datascience community. We guide Datascience enthusiasts on how to enter and excel in this domain. These sessions will not only […].
Introduction DataScience is one of the most promising careers of 2022 and beyond. Do you know that, for the past 5 years, ‘Data Scientist’ consistently ranked among the top 3 job professions in the US market? Keeping this in mind, many working professionals and students have started upskilling themselves.
Each month, ODSC has a few insightful webinars that touch on a range of issues that are important in the datascience world, from use cases of machine learning models, to new techniques/frameworks, and more. So here’s a summary of a few recent webinars that you’ll want to watch. Watch on-demand here. Watch on-demand here.
The answer to this dilemma is Arize AI, the team leading the charge on ML observability and evaluation in production. Part 1 of the webinar series, in partnership with Arize AI, walks you through real-world examples, design patterns, and live demos that bring these concepts to life. Part 3: Can Agents Evaluate Themselves?
From exclusive webinars and hands-on hackathons to live meetups and technical deep dives, this series of events is designed to empower developers, data scientists, and AI enthusiasts to build the next generation of intelligent applications. Ready to explore the cutting edge of artificial intelligence?
Top Insights from ODSC East 2025: 10 Slide Decks Every Data Scientist Should See These slides from ODSC East 2025 offer a snapshot of today’s rapidly evolving data landscape, from lightweight LLMs to production-grade agentic applications. Design, deploy, and scale autonomous AI agents in hands-on, expert-led sessions. 100% Practical.
Learn More ⟶ Talent Assessment Conduct Customized Online Assessments on our Powerful Cloud-based Platform, Secured with Best-in-class Proctoring Learn More ⟶ Research & Advisory AIM Research produces a series of annual reports on AI & DataScience covering every aspect of the industry.
Industry, Opinion, CareerAdvice The Evolving Role of the Modern Data Practitioner In this discussion with Microsofts Marck Vaisman, we talk about the evolution of datascience and what it means to be a data practitioner in 2025 andbeyond. Register now for 40%off!
5 Must-Know Pillars of a DataScience and AI Foundation A datascience and AI foundation needs to be built up properly before diving in head-first. Churn Prevention with Reinforcement Learning Today, churn is the most common datascience problem in the world, because every company wants recurring revenue.
Explore the must-attend sessions and cutting-edge tracks designed to equip AI practitioners, data scientists, and engineers with the latest advancements in AI and machine learning. The ODSC East 2025 Schedule: 150+ AI & DataScience Sessions, Keynotes, &More ODSC East 2025 is THE AI & datascience event of the year!
Datasaur: The Definitive Guide to LLM-Automated Labeling This guide explores how to use Datasaurs LLM Labs to automate data labeling, experiment with multiple models, and utilize robo-labeling to achieve consensus between AI and human annotators. Still, these five datascience methods stand above the rest in this practice.
Just Do Something with AI: Bridging the Business Communication Gap forML This blog explores how ML practitioners can navigate AI business communication, ensuring AI initiatives align with real businessvalue. Looking back at almost 5000 conference sessions, how has the industrychanged? What Can You Do With a Free ODSC East ExpoPass?
If you’re diving into the world of machine learning, AWS Machine Learning provides a robust and accessible platform to turn your datascience dreams into reality. AWS ML removes traditional barriers to entry while providing professional-grade capabilities. Hey dear reader! Hope you’re doing well.
We’re thrilled to announce that we’re partnering with Google to give our community of AI and datascience practitioners even more opportunities to learn, grow, and connect over the next several months. Register for free here!
ChatGPT: The Google Killer, Distributed Training with PyTorch and Azure ML, and Many Models Batch Training Distributed Training with PyTorch and Azure ML Continue reading to learn the simplest way to do distributed training with PyTorch and Azure ML. Learn more about the work they’re doing here!
Using Graphs for Feature Engineering, Prompt Fine-Tuning for Generative AI, and Confident DataScience GraphReduce: Using Graphs for Feature Engineering Abstractions This tutorial demonstrates an example feature engineering process on an e-commerce schema and how GraphReduce deals with the complexity of feature engineering on the relational schema.
During a recent ODSC webinar , Sean Tracey, Head of Developer Relations at Expanso, presented a compelling vision for running large language models (LLMs) securely, efficiently, and locally. Olama abstracts model complexity and provides a clean API for interaction. Models ran efficiently on local CPUs or GPU hardware.
Faster Training and Inference Using the Azure Container for PyTorch in Azure ML If you’ve ever wished that you could speed up the training of a large PyTorch model, then this post is for you. In this post, we’ll cover the basics of this new environment, and we’ll show you how you can use it within your Azure ML project.
It is often too much to ask for the data scientist to become a domain expert. However, in all cases the data scientist must develop strong domain empathy to help define and solve the right problems. Nina Zumel and John Mount, Practical DataScience with R, 2nd Ed.
DataScience & AI News New Breakthrough by Google DeepMind Unveils New Materials According to a new research paper, Google’s DeepMind has discovered hundreds of thousands of new hypothetical material designs. Need some help convincing your manager to send you to ODSC East this April?
The Essential Tools for ML Evaluation and Responsible AI There are lots of checkmarks to hit when developing responsible AI, but thankfully, there are many tools for ML evaluation and frameworks designed to support responsible AI development and evaluation. Learn how Informa’s IIRIS team manages data from over 2.5
There are countless blockers that may keep you from getting your ML projects off the ground, including: The time required to understand and stitch together a fragmented ecosystem of low-level, ML-specific packages. The need for datascience expertise to implement modeling strategies that produce useful results.
Going into developing machine learning models with a hands-on, data-centric AI approach has its benefits and requires a few extra steps to achieve. What Industries are Hiring for Different Jobs in AI Different datascience and AI job titles are suitable for various niches and industries. Here’s how to get there.
Industry, Opinion, Career Advice The Tradeoff Between Complexity and Ground Truth in AI: What You Need to Know Here, we focus on ground truth in AI and what stakeholders need to know to be effective partners with datascience teams. These scary good prices won’t last long! Register now for 30% off.
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.
5 Concerns for ML Safety in the Era of LLMs and Generative AI The growth of large language models and generative AI has spurred new concerns for ML safety and cybersecurity. 5 Data Engineering and DataScience Cloud Options for 2023 AI development is incredibly resource intensive. Register by Friday to save 20%.
Everyone knows Microsoft, as before they were a leader in datascience and AI, they were a leader in software and technology — and still are. Over the years, ODSC has developed a close relationship with them, working together to host webinars, write blogs, and even collaborate on sessions at ODSC conferences.
This presents a challenge, as high-quality labeled training data remains the primary blocker of machine learning projects—at least according to poll data collected from The Future of Data-Centric AI 2023 attendees. Look at our events page to sign up for research webinars, product overviews, and case studies.
Best Financial Datasets for AI & DataScience in2025 Whether its algorithmic trading, risk assessment, fraud detection, credit scoring, or market analysis, the accuracy and depth of financial datasets can make or break an AI-driven solution. Register now for 30%off!
Amazon SageMaker Studio – It is an integrated development environment (IDE) for machine learning (ML). ML practitioners can perform all ML development steps—from preparing your data to building, training, and deploying ML models. The solution design consists of two parts: data indexing and contextual search.
ML for Big Data with PySpark on AWS, Asynchronous Programming in Python, and the Top Industries for AI Harnessing Machine Learning on Big Data with PySpark on AWS In this brief tutorial, you’ll learn some basics on how to use Spark on AWS for machine learning, MLlib, and more.
Data Integrity: The Foundation for Trustworthy AI/ML Outcomes and Confident Business Decisions Let’s explore the elements of data integrity, and why they matter for AI/ML. In this post, we’ll be demonstrating two deep learning approaches to sentiment analysis, specifically using spaCy.
Welcome to AI Makerspace: Building the Future of Agentic LLM Applications Learn how AI Makerspace teaches data scientists to build production-ready LLM apps using agents, RAG, LangGraph, andmore. Design, deploy, and scale autonomous AI agents in hands-on, expert-led sessions. Learn real-world skills. Use cutting-edge tools. 100% Practical.
And before the hackathon starts, make sure to begin your journey with NVIDIA’s exclusive webinar. Bright Data : Ideal for data professionals needing large-scale data acquisition, Bright Data provides AI-driven web scraping and proxy solutions.
The NVIDIA AI Hackathon at ODSC West, Reinforcement Learning for Finance, the Future of Humanoid AI Robotics, and Detecting Anomalies Unleash Innovation at the NVIDIA AI Hackathon at ODSC West 2024 Ready to put your datascience skills to the test? Reinforcement Learning for Finance — Insights from Yves J.
LLMs are quickly changing the landscape of society and the datascience industry, but do you know how to use them? Machine Learning Made Simple with Declarative Programming Tue, Mar 21, 2023 12:00 PM — 1:00 PM EDT Join this webinar and demo to learn about declarative ML systems, incl.
Accelerating Decisions with Third-Party Data in Financial Services On-Demand Webinar Your ability to make confident decisions based on relevant factors relies on accurate data filled with context. That’s why enriching your analysis with trusted, fit-for-use, third-party data is key to ensuring long-term success.
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