AGENDA
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Some talks are pre-recorded due to speakers’ time-zone differences
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Artificial Intelligence
10:10 — 11:05
"The Brief Wondrous Life of AI - Putting ML Models to Bed"
Bojan Miletic
11:05 — 11:45
"Exploring AI pipelines with Elyra and Kubeflow"
Masa Abushamleh
11:45 — 12:25
Q&A
Machine Learning
12:30 — 13:00
"The Importance of Interpretable Machine Learning"
Serg Masis
13:00 — 13:50
"Building smarter solutions with no expertise in machine learning"
Laurent Picard
13:50 — 14:30
"Audio Event Detection with Machine Learning"
Jon Nordby
14:30 — 15:10
Q&A
Break - 5 minute
Data Science
15:15 — 15:55
"Rethinking Personas with LDA"
Tovio Roberts
15:55 — 16:25
"Tranquilizer: Create REST APIs with Jupyter Notebooks with one line"
Albert DeFusco
16:25 — 17:05
"Microservices & Docker for Data Science"
Ayon Roy
17:45 — 18:25
Q&A
Break - 5 minute
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10:00 — 10:10
Intro
Entry-level track
Gives access to Junior track only with no recordings. Focuses on entry-level content around Python.
"Introduction to deep learning and artificial neural networks - inspired by the human brain."
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17:05 — 17:45
Samaya Madhavan
Data Science
Artificial Intelligence
12:55 — 13:25
"An E-commerce Transformer-based Decision-making Recommender"
13:25 — 14:05
"CLAIMED, a visual and scalable component library for Trusted AI"
Romeo Kienzler
14:05 — 14:45
"Operations Research - The lost Data Science"
John Curry
14:45 — 15:25
Q&A
Break - 5 minute
Machine Learning
15:30 — 16:10
"Enhance Performances with Uncertainty"
Samuel Rochette
16:10 — 16:50
"GPU-accelerated recommender systems - from ETL to Training to Production with Python and TensorFlow"
Benedikt Schifferer
Ronay Ak
16:50 — 17:30
"Inferring & Explaining New Knowledge from Knowledge Graphs"
Carolin Lawrence
17:30 — 18:10
Q&A
Break - 5 minute
10:10 — 10:50
"Data data everywhere, No time to think ????"
Aman Sharma
10:50 — 11:30
"Decision Science with Python"
Mattia Ferrini
11:30 — 12:10
"Exploratory Data Analysis (EDA) using Python"
Kautilya Katariya
12:10 — 12:50
Q&A
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10:00 — 10:10
Intro
Full Access
Gives access to Junior track only with no recordings. Focuses on entry-level content around Python.
18:10 — 18:50
PANEL DISCUSSION
Denis Rothman
Artificial Intelligence
11:40 — 12:35
"The Brief Wondrous Life of AI - Putting ML Models to Bed"
Bojan Miletic
12:35 — 13:10
"Exploring AI pipelines with Elyra and Kubeflow"
Masa Abushamleh
13:10 — 13:50
Q&A
Machine Learning
17:10 — 18:00
"Building smarter solutions with no expertise in machine learning"
Laurent Picard
18:00 — 18:30
"Investigation of an Orthogonal Encryption Technique for Deep Learning"
Thien Ngo Le
18:30 — 19:10
"Apriori Unification Pattern for Efficient ML"
Ravishankar Nair
19:50 — 20:30
Q&A
Break - 5 minute
Data Science
14:35 — 15:15
"Rethinking Personas with LDA"
Tovio Roberts
15:15 — 15:55
"Introduction to deep learning and artificial neural networks - inspired by the human brain."
Samaya Madhavan
15:55 — 16:25
"Microservices & Docker for Data Science"
Ayon Roy
16:25 — 17:05
Q&A
Break - 5 minute
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11:30 — 11:40
Intro
Entry-level track
Gives access to Junior track only with no recordings. Focuses on entry-level content around Python.
"Tranquilizer: Create REST APIs with Jupyter Notebooks with one line"
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13:55 — 14:35
Albert DeFusco
19:10 — 19:50
"The Importance of Interpretable Machine Learning"
Serg Masis
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Data Science
Break - 5 minute
Machine Learning
17:05 — 17:45
"Enhance Performances with Uncertainty"
Samuel Rochette
17:45 — 18:15
"Inferring & Explaining New Knowledge from Knowledge Graphs"
Carolin Lawrence
18:15 — 18:55
"GPU-accelerated recommender systems - from ETL to Training to Production with Python and TensorFlow"
Benedikt Schifferer
18:55 — 19:35
Q&A
Break - 5 minute
12:05 — 12:35
"Data data everywhere, No time to think ????"
Aman Sharma
12:35 — 13:15
"Decision Science with Python"
Mattia Ferrini
13:15 — 13:55
"Spotify's Song Recommender Algorithm using Apache Spark MLib"
Jack Vasylenko
13:55 — 14:35
Q&A
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11:55 — 12:05
Intro
Full Access
Gives access to both Junior and Senior tracks, recordings are included. Focuses on deep tech content around Python.
Artificial Intelligence
14:40 — 15:20
"CLAIMED, a visual and scalable component library for Trusted AI"
15:20 — 15:50
"An E-commerce Transformer-based Decision-making Recommender"
Denis Rothman
15:50 — 16:20
"Operations Research - The lost Data Science"
John Curry
16:20 — 17:00
Q&A
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Romeo Kienzler
The Second Day 09/04
Artificial Intelligence
13:25 — 14:05
"An intuitive introduction into Reinforcement Learning"
Eliran Natan
Machine Learning
15:40 — 16:20
"Machine Learning and Marketing, does that fit together?"
Alexander Möllers
16:20 — 17:00
"Apriori Unification Pattern for Efficient ML"
Ravishankar Nair
17:00 — 17:40
"Beyond OCR: Using deep learning to understand documents"
Eitan Anzenberg
17:40 — 18:20
Q&A
Data Science
10:10 — 10:50
"Intro to Pydantic, Run-Time Type Checking For Your Dataclasses"
Alexander Hultnér
10:50 — 11:30
"Personalising Dinner Using Python!"
Irene Iriarte Carretero
11:30 — 12:00
"The Data Science Manifesto - Lessons from the Zen of Python for Data Science and Machine Learning"
Jack Raifer Baruch
12:40 — 13:20
Q&A
Break - 5 minute
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10:00 — 10:10
Intro
Entry-level track
Gives access to Junior track only with no recordings. Focuses on entry-level content around Python.
Q&A
14:05 — 14:15
12:00 — 12:40
"The Power of A/B Testing"
Bishal Agrawal
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14:55 — 15:40
"Natural Language Processing: Approaching Text"
Srik Gorthy
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14:15 — 14:55
"Working with time in Pandas"
Reuven Lerner
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