AI and ML for Software Engineers: Foundational Insights

Machine Learning (ML) and AI play a key role in modern software, and powers much of what we see and interact with. Each talk in this track covers a foundational area of ML, along with real-life use cases. Attendees will learn how ML works behind-the-scenes with software systems, as well as about tools, platforms, and algorithms that make up the discipline.

From this track


Why Most Machine Learning Projects Fail to Reach Production and How to Beat the Odds

Despite the hype around AI, many ML projects fail, with only 15% of businesses' ML projects succeeding, according to McKinsey. Particularly with the significant investments in large language models and generative AI, only a small portion of companies have managed to realize their true value.

Speaker image - Wenjie Zi

Wenjie Zi

Senior Machine Learning Engineer and Tech Lead @Grammarly


Recommender and Search Ranking Systems in Large Scale Real World Applications

Recommendation and search systems are two of the key applications of machine learning models in industry. Current state of the art approaches have evolved from tree based ensembles models to large deep learning models within the last few years.

Speaker image - Moumita Bhattacharya

Moumita Bhattacharya

Senior Research Scientist @Netflix


Verifiable and Navigable LLMs with Knowledge Graphs

Graphs, especially knowledge graphs, are powerful tools for structuring data into interconnected networks. The structured format of knowledge graphs enhances the performance of LLM-based systems by improving information retrieval and ensuring the use of reliable sources.

Speaker image - Leann Chen

Leann Chen

AI Developer Advocate @Diffbot


No More Spray and Pray— Let's Talk About LLM Evals

The pace of development in AI in the past year or so has been dizzying, to say the least, with new models and techniques emerging weekly. Yet, amidst the hype, a sobering reality emerges: much of these advancements lack robust empirical evidence.

Speaker image - Apoorva Joshi

Apoorva Joshi

AI Developer Advocate @MongoDB

Track Host

Susan Shu Chang

Principal Data Scientist @Elastic, Author of "Machine Learning Interviews"

Susan Shu Chang is a principal data scientist at Elastic, which powers search around the world. Previously, she built machine learning at scale in the fintech, social, and telecom industries. She is the author of Machine Learning Interviews, published by O’Reilly.

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