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You're reading from The Machine Learning Summit 2025 Build the skills to stay job-ready with 20+ expert-led sessions on machine learning, GenAI, and LLMs

Product type Video

Published in Oct 2025

Last Updated in Oct 2025

Publisher Packt

ISBN-13 9781806662258

Length 17hrs 52mins

Edition 1st Edition

Languages

Python

Concepts

Data Science

Authors (24):

Stephen Klein

Imran Ahmad

Kush Varshney

Tivadar Danka

Raphaël MANSUY

Sandipan Bhaumik

Lydia L.R. Ray

Anastasia Tzeveleka

Luca Massaron

Khuyen Tran

Tom Yeh

Serg Masís

Vivekanandan SS

Shankar Narayanan SGS

Aurimas Griciūnas

Hanane D.

Mona M

Eslam Kamal Abdelreheem

Thomas Nield

Alex Merced

Gabriele Venturi

Anthony Alcaraz

Stefan Jansen

Andrea Gioia

+20 more

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Table of Contents (3) Chapters

1. The ML Stack in Action

2. Scaling ML Intelligence FREE CHAPTER

3. Enterprise Generative AI

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Authors (24)

Stephen Klein

Stephen Klein is the Founder and CEO of Curiouser.AI, a values-driven AI advisory helping leaders use generative AI to think more clearly, design with intention, and lead with imagination. He also teaches at UC Berkeley, exploring the intersection of strategy, ethics, and emerging tech. A Harvard MBA and three-time entrepreneur, Klein brings global experience across startups, F500s, and higher ed. Formerly CMO at Dentons innovation arm, he led global AI ethics efforts. He is currently working with Georgetown University Press Publishing to author a book called Age of Meaning: What Life Look Likes In A Post Automation World At Curiouser, hes building Alice, an AI strategic coach that supports thoughtful decision-making. His message: AI isnt just about tecd its about better questions, stronger values, and more human leadership.

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Imran Ahmad

Imran Ahmad is the author of the 50 Algorithms every programmer should know. He has been a part of cutting edge research about algorithms and machine learning for many years. He completed his PhD in 2010, in which he proposed a new linear programming based algorithm that can be used to optimally assign resources in a large scale cloud computing environment. In 2017, Imran developed a real time analytics framework named StreamSensing. He has since authored multiple research papers that use StreamSensing to process multimedia data for various machine learning algorithms. Imran is currently working at Advanced Analytics Solution Center A2SC at the Canadian Federal Government as a data scientist. He is using machine learning algorithms for critical use cases. Imran is a visiting professor at Carleton University, Ottawa. He has also been teaching for Google and Learning Tree for the last few years.

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Kush Varshney

Kush Varshney is a research staff member and manager in IBM Research AI, working from the Thomas J. Watson Research Center. He codirects the IBM Science for Social Good initiative.

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Tivadar Danka

Tivadar Danka is a mathematician by training, a machine learning engineer by profession, and an educator by passion. After finishing his PhD in 2016 about the arcane subject of orthogonal polynomials, he switched career paths and has been working in machine learning ever since. His work includes applying deep learning to cell microscopy images to identify and phenotype cells, creating one of the most popular open source Python packages for active learning, building a full machine learning library from scratch, and collecting about a total of 100k followers on social media, all by posting high quality educational content

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Raphaël MANSUY

Raphael Mansuy is a seasoned technology executive and entrepreneur with over 25 years of experience in software development, digital transformation, and AI driven solutions. As a founder of several companies, he has demonstrated success in designing and implementing mission critical solutions for global enterprises, creating innovative technologies, and fostering business growth. Raphael is highly skilled in AI, data engineering, DevOps, and cloud native development, offering consultancy services to Fortune 500 companies and startups alike. He is passionate about enabling businesses to thrive using cutting edge technologies and insights.

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Sandipan Bhaumik

Sandipan is a Data & AI Leader at AWS, specializing in building enterprise scale AI solutions. With over 17 years of experience, Sandi advises on strategy, governance, regulatory compliance, and sustainable architectures. He leads global knowledge initiatives, enabling organizations to implement secure, efficient, and responsible AI solutions aligned with long term business and environmental goals. He is currently building a community of AI Agent Builders interested in learning to build and use AI agents at work and in personal life.

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Lydia L.R. Ray

Lydia Ray is an AWS expert in Data and AI solutions, building scalable, cost effective analytics and ML platforms for the media, entertainment, sports, betting and gaming industries. With 10+ years experience across startups and Fortune 100s, she blends technical expertise with industry insight. Lydia is passionate about ethical AI and inclusive tech, and is a hands on innovator and advocate for inclusive data communities, creating spaces to grow, share, and collaborate around responsible AI.

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Anastasia Tzeveleka

Anastasia is a Sr. GenAI/ML Specialist Solutions Architect at AWS. In her current role, she works with Financial Services customers helping them transform complex business challenges into powerful AI-driven solutions. Anastasia has extensive experience in AI, having worked with government and research organizations across EMEA helping them pre-train and fine-tune large language models on AWS. Before that, she pioneered voice experiences at Amazon Alexa, collaborating with brands to create engaging customer interactions through conversational AI

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Luca Massaron

Luca Massaron is a data scientist with over a decade of experience in transforming data into high impact, innovative artifacts, solving real world problems, and generating value for businesses and stakeholders. He is the author of numerous bestselling books on AI, machine learning, and algorithms. Luca is also a 3x Kaggle Grandmaster who reached number 7 in the worldwide user rankings for his performance in data science competitions. Additionally, he is recognized as a Google Developer Expert GDE in AI, Kaggle, and the cloud.

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Khuyen Tran

Khuyen Tran is a Developer Advocate at Nixtla. She wrote over 180 data science articles with over 100k views per month on Towards Data Science and published over 800 daily tips related to data science and Python at CodeCut. Her current mission is to make open source tools more accessible to the data science community and to educate data scientists on optimal engineering practices for data science projects.

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Tom Yeh

Tom Yeh is an Associate Professor of Computer Science at the University of Colorado Boulder, specializing in human computer interaction and its societal impacts.

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Serg Masís

For the last two decades, Serg Masis has been at the confluence of the internet, application development, and analytics. Currently, he is a Climate and Agronomic Data Scientist at Syngenta, a leading agribusiness company with a mission to improve global food security. Before that role, he co founded a search engine startup incubated by Harvard Innovation Labs, combining the power of cloud computing and machine learning with principles in decision making science to expose users to new places and events efficiently. Whether it pertains to leisure activities, plant diseases, or customer lifetime value, Serg is passionate about providing the often missing link between data and decision making and machine learning interpretation helps bridge this gap more robustly.

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Vivekanandan SS

Vivekanandan leads the GenAI Prompt Engineering team at Verizon, leveraging over a decade of expertise in Data Science and Big Data. His professional journey includes building analytics solutions and products across diverse domains, with proficiency in cloud analytics and data warehouses. As an experienced trainer, he specializes in Snowflake and GenAI, and serves as a guest faculty and advisor for various educational institutes. Notably, his solution ranks in the top 1 percentile globally in Kaggle Kernels.

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Shankar Narayanan SGS

Shankar Narayanan is a Technical Architect with over a decade of diverse experience leading and delivering large scale Data and Cloud implementations for Fortune 500 companies across various industries. He has successfully implemented Snowflake Data Cloud for many organizations leading the customers to adopt Snowflake. He holds a bachelors and masters degree in Computer science and holds many certifications in multi cloud platforms and Snowflake. He is an award winning blogger and actively contributes to various technical publications and open source projects. For his technical contribution to the community, He has been selected as SAP Community Topic leader by SAP and is selected as one of the 72 Snowflake Data Heroes by Snowflake

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Aurimas Griciūnas

Aurimas Griciunas is a recognized AI expert, LinkedIn Top Voice in AI, and the founder of SwirlAI. He previously served as Chief Product Officer at Neptune.ai where he worked closely with top ML teams to scale infrastructure, evaluation, and LLMOps practices across industries. With over a decade of experience at the intersection of data science, machine learning, and software engineering, Aurimas has led AI initiatives in both startups and enterprise environments. His mission is to bridge the gap between hype and reality by teaching engineers how to build systems that work in the real world.

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Hanane D.

Hanane Dupouy is Director and Algorithmic Trader at Bernstein, where she designs and implements equity trading strategies to execute client orders with precision and efficiency. She holds an engineering degree and a specialized masters in finance from leading French business schools, and began her career managing a team of data scientists and business intelligence professionals at a major French bank. Over the past six years, Hanane has transitioned fully into algorithmic trading, leveraging machine learning, generative AI, AI agents, and retrieval augmented generation RAG to build and optimize trading systems that adapt to rapidly changing market conditions. Outside of trading, Hanane shares her expertise through her blog,machinelearning basics.com, where she provides in depth tutorials on technical indicators, AI driven finance, and algorithmic trading best practices. She is also a frequent speaker at industry events, including the CFA UK Technology & Innovation Skills webinars, discussing the practical application of AI frameworks in financial contexts. A CFA charterholder, Hanane combines technical rigor with strategic vision to bridge the gap between cutting edge technology and practical business solutions.

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Mona M

Mona currently works as a Sr WW Gen AI Specialist Solutions Architect at Amazon focusing on Gen AI Solutions. She was a Lead Generative AI specialist in Google Public Sector at Google before joining Amazon. Mona is a published author of two books Natural Language Processing with AWS AI Services Derive strategic insights from unstructured data with Amazon Textract and Amazon Comprehend and Google Cloud Certified Professional Machine Learning Study Guide. Her first book is in course curriculum of Georgia State University Masters in Computer Information Systems program and She has been a guest Lecturer to the program. She has authored 19 blogs on AI ML and cloud technology and a co author on a research paper on CORD19 Neural Search which won an award for Best Research Paper at the prestigious AAAI Association for the Advancement of Artificial Intelligence conference. Mona Mona is a member of SWE Society for women engineers and she mentors early career graduates looking to pursue careers in AI and Cloud Computing. She is also a frequent speaker at multiple conferences such as ISMB 2022, AWS Re Invent 2020,2019,2018 and AWS DC Summit

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Eslam Kamal Abdelreheem

Eslam Kamal is an AI Engineering and Applied Science Manager with 18+ years of professional experience, currently at Meta and Ex Microsoft. His focus areas include Multimodal LLMs, Conversational AI, NLP, Responsible AI and ML Data Strategies. Eslam is responsible for the conversational quality of Live AI models on Ray Ban Meta smart glasses and next gen smart wearables. Previously, he led applied science and engineering teams for Azure Responsible AI, GitHub Copilot, Microsoft Copilot, Copilot Studio, Dynamics 365, and Azure AI Language, and worked on various NLP problems including multilingual NLU and machine translation.

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Thomas Nield

Thomas Nield is the founder of Nield Consulting Group as well as an instructor at OReilly Media and University of Southern California. He enjoys making technical content relatable and relevant to those unfamiliar or intimidated by it. Thomas regularly teaches classes on data analysis, machine learning, mathematical optimization, and practical artificial intelligence. At USC he teaches AI System Safety, developing systematic approaches for identifying AI related hazards in aviation and ground vehicles. Hes authored two books, including Getting Started with SQL OReilly and Learning RxJava Packt.

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Alex Merced

Alex Merced is the Head of DevRel at Dremio with experience as a developer and instructor. His professional journey includes roles at GenEd Systems, Crossfield Digital, CampusGuard, and General Assembly. He co authored Apache Iceberg The Definitive Guide published by OReilly and has spoken at notable events such as Data Day Texas and Data Council. Alex is passionate about technology, sharing his expertise through blogs, videos, podcasts like Datanation and Web Dev 101, and contributions to the JavaScript and Python communities with libraries like SencilloDB and CoquitoJS.

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Gabriele Venturi

Gabriele is a serial entrepreneur and software engineer, and the founder of PandasAI and PandaAGI open source platforms dedicated to building explainable, programmable, and secure AI agents capable of operating on real data and infrastructure. A Y Combinator alum, he has launched and scaled multiple startups and collaborated with Fortune 500 companies to bring AI into production and automate complex workflows. Gabriele is driven by a mission to create AI tools that developers can trust bridging the gap between research and real world applications through deterministic design, full transparency, and a focus on practical developer experience.

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Anthony Alcaraz

As AWS Senior AI ML Strategist for EMEA Startups, Anthony specializes in guiding early stage AI companies through technical development and go to market strategies. His experience encompasses a wide range of cutting edge domains, including large language models, generative AI architectures, knowledge graphs, vector spaces, MLOps, and agentic AI systems. He has led AI strategy for venture backed startups, built and scaled machine learning platforms for enterprise clients, and lectured at Oxford on the latest in LLM and graph based solutions. Alongside providing rigorous technical due diligence for AI investments, he helps optimize architectures on AWS AI ML services, craft GTM strategies, and evaluate generative AI applications. His passion lies in empowering founders and investors to successfully navigate the complexities of building transformative AI companies, offering deep technical evaluation, architectural guidance, and strategic insights geared toward accelerating startup success.

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Stefan Jansen

Stefan is the founder and CEO of Applied AI. He advises Fortune 500 companies, investment firms, and startups across industries on data & AI strategy, building data science teams, and developing end to end machine learning solutions.

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Andrea Gioia

Andrea Gioia is a partner and CTO at Quantyca, a consulting firm specializing in data management, and co founder of blindata.io, a SaaS platform for data governance and compliance. With over 20 years of experience, Andrea has led cross functional teams delivering complex data projects across multiple industries. As CTO, he advises clients on defining and executing their data strategies. Andrea is a frequent speaker and writer, serving as the main organizer of the Data Engineering Italian Meetup and leading the Open Data Mesh Initiative. He is an active DAMA member and has been part of the DAMA Italy Chapters scientific committee since 2023.

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You're reading from The Machine Learning Summit 2025 Build the skills to stay job-ready with 20+ expert-led sessions on machine learning, GenAI, and LLMs

Table of Contents (3) Chapters

Authors (24)

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