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Big data analytics is evergreen, and as more companies use big data it only makes sense that practitioners are interested in analyzing data in-house. Deeplearning is a fairly common sibling of machine learning, just going a bit more in-depth, so ML practitioners most often still work with deeplearning.
First, there’s a need for preparing the data, aka data engineering basics. Machine learning practitioners are often working with data at the beginning and during the full stack of things, so they see a lot of workflow/pipeline development, datawrangling, and data preparation.
Finally, Tuesday is the first day of the AI Expo and Demo Hall , where you can connect with our conference partners and check out the latest developments and research from leading tech companies. This will also be the last day to connect with our partners in the AI Expo and Demo Hall.
Jon Krohn (Duration: ~6 hrs) Pre-Bootcamp Live Virtual Training In addition to the on-demand training, you’ll also have the opportunity to attend 5 live virtual training sessions on fundamental data science skills as part of our ODSC Bootcamp Primer series. Day 1 will focus on introducing fundamental data science and AI skills.
ODSC West is less than a week away and we can’t wait to bring together some of the best and brightest minds in data science and AI to discuss generative AI, NLP, LLMs, machine learning, deeplearning, responsible AI, and more. Join the Solution Showcases to learn how your organization can build AI better.
Well, the thing is AI allows for advanced techniques to analyze data and make sophisticated predictions based on data. AI algorithms are the foundation of machine learning, deeplearning, and NLP — all fields that are currently revolutionization our technological landscape.
There are some people in deeplearning today who say you can do anything with backpropagation. I have this ongoing discussion with one person who says gradient descent is the only thing you need for deeplearning. There are people at one end of the spectrum who say that paradigm is all you need.
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. DataWrangling: Data Quality, ETL, Databases, Big Data The modern data analyst is expected to be able to source and retrieve their own data for analysis.
Access a full range of industry-focused data science topics from machine learning/deep pearling, to NLP, popular frameworks, tools, programming languages, datawrangling, and all the skills you need to know. It’s a free event that no data pro should miss! That’s why at ODSC East, we have the AI Expo.
A quick demo of our app working is shown below: The Flask development server (Werkzeug’s Web Server Gateway Interface (WSGI) server) is unsuitable for production as it can only handle one request at a time. ', port = port) Our flask app — app.py We’re committed to supporting and inspiring developers and engineers from all walks of life.
Jon Krohn, Host of the SuperDataScience Podcast Jon Krohn is a leading voice in data science as the host of SuperDataScience, the industrys most-listened-to podcast. A prolific researcher with over 20 published papers, 1,000+ citations, and 20 patents, his expertise spans deeplearning, interpretability, and sports analytics.
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