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Machine Learning & Deep Learning
The Machine Learning & Deep Learning Conference is where experts in the rapidly expanding fields of Deep Learning and Machine Learning gather to discuss the latest advances, trends, and models in this exciting field.
Attend talks, tutorials, and workshops and hear from the creators and top practitioners as they demonstrate and teach the latest developments in Machine Learning and Deep Learning that solve problems in business and society today.
What You'll Learn
Talks & Workshops on these topics:
Topics
Machine Learning
Deep Learning
Artificial Intelligence
Neural Networks
Natural Language Processing
Computer Vision
Pattern Recognition
Tools & Languages
R
Python SciPy, Pandas, etc
Scikit-learn
Tensorflow
Spark
MLlib
H20
Tools & Languages
WEKA
Pylearn2
Theano
Caffe
Torch
Azure Machine Learning API
and many more..
ODSC APAC Virtual Conference 2024
Register your InterestSome of Our Confirmed Machine Learning and Deep Learning Speakers
Eve Psalti
Eve Psalti is 20+year tech and business leader, currently the Senior Director at Microsoft’s Azure AI engineering organization responsible for scaling & commercializing artificial intelligence solutions.
She was previously the Head of Strategic Platforms at Google Cloud where she worked with F500 companies helping them grow their businesses through digital transformation initiatives.
Prior to Google, Eve held business development, sales and marketing leadership positions at Microsoft and startups across the US and Europe leading 200-people teams and $600M businesses.
A native of Greece, she holds a Master’s degree and several technology and business certifications from London Business School and the University of Washington. Eve currently serves on the board of WE Global Studios, a full-stack startup innovation studio supporting female entrepreneurs.
Infuse Generative AI in your Apps Using Azure OpenAI Service(Keynote)
Kerrie Mengersen, PhD
Kerrie Mengersen is a Distinguished Professor of Statistics and Director of the Centre for Data Science at QUT. Her career in statistical consulting and academic research has taken her across three states of Australia, the USA and France. Kerrie is a Fellow of the Australian Academy of Science, the Australian Academy of Social Sciences, and the Queensland Academy of the Arts and Sciences. Her overall ambition is to ‘use data better’, particularly in the fields of health, environment and industry. To this end, she has led over 30 major projects such as the current Long-term Benefits and Impacts Study with Queens Wharf Brisbane, the online interactive Australian Cancer Atlas and the Virtual Reef Diver program.
Making Private Data Open and Enhancing Decision-Making through Digital Atlases(Talk)
Hugo Bowne-Anderson, PhD
Hugo Bowne-Anderson is a data scientist, writer, educator & podcaster. His interests include promoting data & AI literacy/fluency, helping to spread data skills through organizations and society and doing amateur stand up comedy in NYC. He does many of these at DataCamp, a data science training company educating over 3 million learners worldwide through interactive courses on the use of Python, R, SQL, Git, Bash and Spreadsheets in a data science context. He has spearheaded the development of over 25 courses in DataCamp’s Python curriculum, impacting over 170,000 learners worldwide through my own courses. He hosts and produce the data science podcast DataFramed, in which he uses long-format interviews with working data scientists to delve into what actually happens in the space and what impact it can and does have. He earned PhD in Mathematics from the University of New South Wales, Australia and has conducted biomedical research at the Max Planck Institute in Germany and Yale University, New Haven.
Helen Thompson
Helen Thompson is an Associate Professor of Statistics in the School of Mathematical Sciences and the Centre for Data Science at QUT. She specialises in statistical modeling and machine learning. With expertise in high-dimensional data analysis, space-time modeling, and optimum experimental design, she has made significant contributions to various fields including health, environment, and social sciences. She has published extensively in leading journals and her work provides valuable insights into complex datasets, uncovering hidden patterns and informing optimal decision-making processes in projects including Optimal Resource Extraction with BHP, Emergency Department Demand Modelling with Queensland Metro South Health and Hospital Services, Great Barrier Reef monitoring programs, and the Australian Cancer Atals.
Making Private Data Open and Enhancing Decision-Making through Digital Atlases(Talk)
Ville Tuulos
Ville has been developing infrastructure for machine learning for over two decades. He has worked as an ML researcher in academia and as a leader at a number of companies, including Netflix where he led the ML infrastructure team that created Metaflow, a popular open-source framework for data science infrastructure. He is a co-founder and CEO of Outerbounds, a company developing modern human-centric ML. He is also the author of the book Effective Data Science Infrastructure, published by Manning.
Human-Friendly, Production-Ready Data Science with Metaflow(Talk)
A M Aditya
Aditya is a tech enthusiast with more than 7 years of experience across various technologies in data science, machine learning, deep learning and computer vision. He has completed his Masters in Data Science from the National University of Singapore. He has worked across various domains including automotive, banking, retail among others consulting various clients around the globe. He is a true believer of ‘You got to see it work to know it works’ and sets goals towards achieving the same in any of the endeavours he undertakes. Being highly inclined towards technology, he founded Xaltius Pte. Ltd in Singapore which has a major focus on building solutions in Data Science and AI and educating students and professionals in the same areas. He also founded Code for India which specializes in delivering top notch skills in Data Science and AI as required in the industry today. Apart from work, he loves to engage with kids and get involved in social work.
Vaishali Balaji
Vaishali is a lead data scientist at Indium Software, a leading digital engineering company. She has 9 years of experience in the advanced analytics domain. She manages a large data science team, does project planning and builds enterprise grade analytics models for various real-world usecases. As a technology evangelist, Vaishali also coaches aspiring professionals on data science, machine learning and various advanced analytics technologies like natural language processing, computer vision, deep learning etc., She holds a professional postgraduate in Artificial Intelligence & Machine Learning.
Transformers for Document Understanding(Tutorial)
Xander Song
Xander Song is a Machine Learning Engineer and Developer Advocate at Arize AI and one of the creators of Phoenix, a popular notebook-first python library that leverages embeddings to uncover problematic cohorts of LLM, CV, NLP and tabular models. Before joining Arize, Song worked as a machine learning engineer at early stage AI startups. He is based in Oakland, California.
Suman Debnath
Suman Debnath is a Principal Developer Advocate (Data Engineering) at Amazon Web Services, primarily focusing on Data Engineering, Data Analysis and Machine Learning. He is passionate about large scale distributed systems and is a vivid fan of Python. His background is in storage performance and tool development, where he has developed various performance benchmarking and monitoring tools.
Build Classification and Regression Models with Spark on AWS(Workshop)
Bharti Motwani
Bharti Motwani is the sole author of many books “Data Analytics with R” (Wiley), “Data Analytics using Python” (Wiley), “HR Analytics: Practical Approach using Python” (Wiley), “Machine Learning for Text and Image data: Practical Approach with Business Use Cases”
(Wiley) etc. Ambitious and analytical professional; IT and analytics consultant and corporate trainer; Result driven and articulate academician who can think “out of the box”, with more than 25 years of experience in teaching at professional and premium institutes at global level, research and software development. Demonstrated proficiency in writing books, editing and reviewing journals, and writing more than 50 research papers in leading international and national journals.
Big Data Analysis with PySpark (Workshop)
Habib Baluwala
Habib Baluwala, a dedicated data leader with a PhD from Oxford, serves as the Domain Chapter Lead at Spark New Zealand. With over 15 years of experience in data engineering and data science, he has developed a deep understanding of how data can drive business success. Habib’s exceptional leadership and communication skills enable him to effectively engage with stakeholders, lead high-performing teams, and drive data-driven decision-making across the organization. He actively explores AI governance for responsible and ethical AI implementation. Committed to continuous learning and teamwork, his expertise is exemplified by his Chief Data Officer certification. A seasoned leader, Habib’s unique combination of technical expertise and leadership skills empowers him to deliver innovative data solutions that support business growth.
Danni Li
Danni Li is an AI Resident at Meta. She is interested in building efficient AI systems and applications to solve real-world problems. Her current research focuses on on-device ASR models and optimization techniques.
Why Attend
Immerse yourself in talks, tutorials, and workshops on Machine Learning and Deep Learning tools, topics, models, and advanced trends
Expand your network and connect with like- minded attendees to discover how Machine Learning and Deep Learning knowledge can transform not only your data models but also your business and career
Meet and connect with the core contributors and top practitioners in the expanding and exciting fields of Machine Learning and Deep Learning
Learn how the rapid rise of intelligent machines is revolutionizing how we make sense of data in the real world and impacting the domains of business, society, healthcare, finance, manufacturing, and more
Featured Sessions
Machine Learning with R
Deep Learning with Tensorflow for Absolute Beginners
Deep Learning for Developers
Small to Big Data and Deep Learning
Leveraging Better User Experience through Chatbots
Guided Generative Adversarial Neural Network
Deep Learning in Keras
Distributed Deep Learning on Hops
Deep Learning with MXnet
Recommendation System Architecture and Algorithms
Who will attend
Top speakers and practitioners in Machine Learning and Deep Learning
Data Scientists and Data Analysts
Decision makers
Software Developers focused on Machine Learning and Deep Learning
Data Science Innovators
CEOs, CTOs, CIOs
Industry leaders
Core contributors in the fields of Machine Learning and Deep Learning
Data Science Enthusiasts
ODSC Newsletter
Stay current with the latest news and updates in open source data science. In addition, we’ll inform you about our many upcoming Virtual and in person events in Boston, NYC, Sao Paulo, San Francisco, and London. And keep a lookout for special discount codes, only available to our newsletter subscribers!