About Jason Bell

Jason Bell is a seasoned machine learning practitioner, author, and strategic advisor with over 15 years of experience bridging the gap between theoretical AI concepts and real-world implementation and over 35 years in software. His expertise spans quantitative analysis, data science, and startup strategy, making him a sought-after voice in the intersection of technology and business innovation. Jason's practical approach to machine learning has helped organisations across industries leverage AI to drive growth and competitive advantage.

As an accomplished author, Jason has written extensively on machine learning for technical audiences. His flagship work, "Machine Learning: Hands On For Developers and Technical Professionals," published by Wiley in 2014 with a second edition in 2020, has become required reading at over 35 universities worldwide, including Columbia, NYU, UC San Diego, and Purdue. He also contributed to "Machine Learning and the City: Applications in Architecture and Urban Design" (2022), demonstrating his ability to apply ML concepts across diverse domains. Beyond his books, Jason maintains an active writing presence through his long-running blog "It's All A Bet" (2008-2023) and regular contributions to Medium, where he shares insights on quantitative methods, AI strategy, and the evolving landscape of data-driven decision making.

Currently serving as an advisor to startups and established companies, Jason helps organisations navigate the complexities of AI implementation, from building effective data science teams to developing comprehensive ML strategies. His unique combination of hands-on technical expertise, academic credibility, and business acumen makes him an invaluable resource for companies looking to harness the power of machine learning and artificial intelligence in their operations.