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Upcoming events (3)

DataHour: Introduction to Interpretable Machine Learning

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About the DataHour:
Interpretable machine learning is needed because machine learning by itself is incomplete as a solution. The complex problems we solve with machine learning aren't solvable through conventional software engineering. By explaining a model's decisions, we can cover gaps in our understanding of the problem, and its corresponding solution.
Black-box machine learning models are thought to be impenetrable. However, with inputs and outputs alone, a lot can be learned about the reasoning behind their predictions. In this DataHour, we will cover the importance of model interpretation and explain various methods and their classifications, including feature importance, feature summary, and local explanations using Python.

Prerequisites: Basic python and some fundamental idea of Machine Learning.

Who is this DataHour for?
Students and Freshers with an interest in Data Science.
Data science professionals who want to accelerate their career growth

Speaker:
Serg is a data scientist in agriculture with a lengthy background in entrepreneurship and web/app development, and the author of the bestselling book "Interpretable Machine Learning with Python". Passionate about machine learning interpretability, responsible AI, behavioral economics, and causal inference.
You can follow him on Linkedin and Twitter.

Speaker: Serg Masís
Designation: Climate & Agronomic Data Scientist at Syngenta

DataHour: Building NLP applications using Hugging Face

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About the DataHour:
As amazing as state-of-the-art machine learning models are, training, optimizing, and deploying them remains a challenging endeavor that requires a significant amount of time, resources, and skills, all the more when different languages are involved. Unfortunately, this complexity prevents most organizations from using these models effectively, if at all. Instead, wouldn’t it be great if we could just start from pre-trained versions and put them to work immediately?
This is the exact challenge that Hugging Face is tackling. Its tools make it easy to add state-of-the-art Transformer models to your applications. Thanks to the open-source libraries of Hugging Face, developers can easily work with 5,000+ datasets and 50,000+ pre-trained models in 160+ languages. In fact, with over 65,000 stars on GitHub, the transformers library has become the de-facto tool for developers and data scientists who need state-of-the-art models for natural language processing, computer vision, and speech.
In this DataHour, Julien will introduce you to Transformer models and what business problems you can solve with them. Then, he’ll show you how you can simplify and accelerate your machine learning projects end-to-end: experimenting, training, optimizing, and deploying. Along the way, he’ll run some demos to keep things concrete and exciting!

Prerequisites: Enthusiasm for learning and basic concepts of Machine Learning & Python.

Who is this DataHour for?
Students and Freshers with an interest in Data Science.
Data science professionals who want to accelerate their career growth

Speaker:
Julien is currently Chief Evangelist at Hugging Face. He's recently spent 6 years at Amazon Web Services where he was the Global Technical Evangelist for AI & Machine Learning. Prior to joining AWS, Julien served for 10 years as CTO/VP Engineering in large-scale startups.
You can follow him on Linkedin, Twitter and Youtube.

Speaker: Julien Simon
Designation: Chief Evangelist at Hugging Face

1729- A Category Defining AI Event

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Bringing to you the ultimate event in the realm of AI. An event where industry leaders from the various verticals of AI come together to talk about everything that has been and will be in the world of AI.

Come join us for 40 Speakers, 11 Keynotes & Power Talks, 4 Hands-on Workshops and 19 deep-dive sessions.

Be there at the most awaited AI event, 1729.

LINK: https://bit.ly/3zI8PqG

Past events (70)

DataHour: Introduction to Image Processing using Python

This event has passed

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