Mastering MLOps with Maria: Insights and Future Trends

Join us for an in-depth conversation with Maria, a leading expert in MLOps, as she shares her journey and insights into the world of machine learning operations. Maria discusses the common misconceptions about MLOps, the integration of DevOps practices, and the tools and frameworks that have shaped her career. Discover her unique approach to MLOps, the challenges faced by data science teams, and the evolution of the field. Maria also introduces her new course on MLOps with Databricks, aimed at helping practitioners deepen their skills. Don't miss this episode for valuable advice and a peek into the future of MLOps!

0:00 Intro

0:31 Marvel and Lego: A Personal Touch

1:12 Journey into MLOps

02:09 The Evolution of MLOps

04:38 Challenges and Best Practices in MLOps

06:38 MLOps vs. DevOps

08:10 LLM Monitoring and Prompt Engineering

10:02 Advice for MLOps Practitioners

13:15 Marvelous MLOps: The Blog and Course

17:53 Final Thoughts and Career Advice

19:21 Conclusion and Farewell

Harpreet Sahota on Becoming a Hacker in Residence & AI Innovation: Chat with Miko Pawlikowski

Join Miko Pawlikowski on HockeyStick as he interviews Harpreet Sahota, Voxel51's Hacker in Residence and a prominent figure in the AI community. Harpreet shares his journey from studying math and stats to becoming a biostatistician and data scientist, eventually taking on his current role. They discuss what it means to be a Hacker in Residence, the importance of Voxel51's open-source library in the AI industry, and Harpreet's upcoming book on Practical Retrieval Augmentation Generation. Harpreet also delves into his experiences with LinkedIn courses, his extensive podcasting history, and advice for aspiring AI professionals. Tune in to learn about the intricate balance of responsibilities in Harpreet's role, from creating educational content to exploring novel AI applications.

00:00 Meet Harpreet Sahota: Hacker in Residence

01:25 Role and Responsibilities at Voxel51

04:59 Journey to Becoming a Hacker in Residence

10:44 Challenges and Rewards of the Role

15:07 Writing a Book on Retrieval Augmented Generation

23:12 Creating LinkedIn Learning Courses

28:17 Balancing Work and Family Life

28:42 Recording Courses from Home

28:56 Choosing Not to Be On-Screen

29:23 Writing and Newsletters

31:07 Industry Events and Conferences

35:00 Traveling for Work

36:10 The Harpreet Podcast

41:59 Future Plans and Building a Dream House

44:25 Final Thoughts and Reflections

45:33 Advice for Aspiring Professionals

Simplifying Algorithms with Vadim Smolyakov!

Get Vadim's book 45% OFF with code hockeystick24 here: https://mng.bz/4J5Q

Join Miko Pawlikowski on HockeyStick as he discusses machine learning algorithms with Vadim Smolyakov, author of 'Machine Learning Algorithms in Depth.' They explore Vadim's experiences at MIT CSAIL, his work at Microsoft, and key machine learning concepts like Bayesian nonparametrics, decision trees, and Markov chain Monte Carlo methods. Vadim also shares insights on his book, the challenges in implementing ML algorithms, and predictions about the future of AI. This episode is perfect for intermediate learners and those new to machine learning.

0:00 Guest Introduction: Vadim Smolyakov

00:48 MIT CSAIL Experience

01:28 Bayesian Inference and Non-Parametrics

02:30 Vadim's Work at Microsoft

03:14 The Origin of Vadim's Book

06:41 Target Audience for the Book

08:04 Explaining Bayesian Algorithms

15:57 Supervised vs Unsupervised Learning

19:22 Decision Trees and Random Forests

24:42 Challenges in Implementing ML Algorithms

31:32 Top Machine Learning Algorithms

45:27 Future of AI and ML

50:31 Conclusion and Farewell

Matt Carey's AI Journey: From Windsurfing to London’s AI Meetups

Join Miko Pawlikowski on HockeyStick as he chats with Matt Carey, an AI engineer at StackOne, AWS Community Builder, organizer of AI Demo Days, and OpenUK AI Advisory Board member. In this episode, Matt shares his unique path from competitive windsurfing to AI engineering, the challenges of transitioning from outdoor sports to indoor coding, and his passion for building a strong AI community in London. They delve into the vibrant AI scene in London, the importance of open-source advocacy, and the exciting innovations happening in Web AI and browser-based LLMs. Matt provides insights into his work with StackOne and offers advice for aspiring AI engineers and startup enthusiasts.

0:00 Introduction to the Episode

0:39 Matt Carey's Windsurfing Journey

1:58 Transition from Windsurfing to AI

4:34 AI Scene in London

5:21 AI Demo Days and Meetups

10:42 AWS Community Builder Experience

14:58 OpenUK AI Advisory Board

18:02 Exciting Innovations in the London Startup Scene

25:51 Navigating Funding and Incubators in London

26:30 Influential Figures and Cool Projects to Follow

28:56 The Role of AI Engineers at StackOne

33:09 The Fun and Chaos of Tech Twitter

Exploring Quantum Computing with Johan Vos!

Get Johan's book 45% OFF with code hockeystick24 here: https://mng.bz/v8da

Join Miko Pawlikowski on HockeyStick as he delves into the fascinating world of quantum computing with Johan Vos, author of "Quantum Computing in Action" and co-founder of Gluon. Discover what makes quantum computing special, its implications for future technology, potential impacts on security, and how to future-proof your career in a quantum-driven world. Johan explains complex concepts like superposition and entanglement in simple terms and discusses real-world applications and the future of quantum hardware. Don't miss this comprehensive guide to understanding the next big leap in computing!

0:00 What Makes Quantum Computing Special?

1:49 Quantum Computing vs Classical Computing

4:17 Real-World Applications of Quantum Computing

6:25 Understanding Qubits and Superposition

10:02 Quantum Entanglement Explained

13:54 Quantum Computing Hardware and Simulators

26:06 Programming Quantum Computers

42:38 Future of Quantum Computing

48:00 Conclusion and Final Thoughts

Think Like a Software Engineering Manager - insights with Akanksha Gupta

Get her book 45% OFF with code hockeystick24 here: https://mng.bz/v8va

Join Miko Pawlikowski on this episode of HockeyStick as he delves into the world of software engineering management with Akanksha Gupta, author of "Think Like a Software Engineering Manager". Explore Akanksha's journey from software engineer to engineering manager and gather valuable insights on making the transition, thriving in the role, and avoiding common pitfalls. Learn about essential skills such as delegation, career discussions, and maintaining team morale, along with practical strategies for hiring, managing attrition, and personal growth.

0:00 Intro

0:24 Meet Akanksha Gupta: Author and Engineering Manager

1:09 The Journey from Engineer to Manager

1:34 Writing the Book: Inspiration and Challenges

4:31 Deciding to Transition: Promotion vs. Lateral Move

9:09 Navigating the People Aspect of Management

15:19 Key Traits of a Good Engineering Manager

34:52 Continuous Learning and Self-Growth

40:00 Final Advice for Aspiring Engineering Managers

Exploring Robo Advisors with Python Experts: Rob Reider & Alex Michalka

Get their book 45% OFF with code hockeystick24 here: https://mng.bz/ngjd

Join Miko Pawlikowski on this episode of HockeyStick as he dives into the world of robo advisors with industry heavyweights Rob Reider and Alex Michalka, authors of "Build a Robo Advisor with Python from Scratch". Discover their fascinating career paths from hedge funds to robo advising, the intricacies of Python programming for finance, and the evolution of financial planning and optimization techniques. Gain insights into asset allocation, tax-loss harvesting, Monte Carlo simulations, reinforcement learning, and the future of robo advising. An essential watch for anyone interested in the intersection of finance and technology!

0:00 Introduction to Robo Advisors

0:50 Rob Reider's Career Journey

01:40 Quantopian and the Love for Python

04:19 The Birth of a Book Collaboration

05:11 Alex's Journey and Weather Derivatives

08:08 Understanding Hedge Funds vs. Robo Advisors

11:13 The Rise of Robo Advisors

17:30 Tax Efficiency and Asset Allocation

24:51 Target Audience and Book Insights

28:21 Monte Carlo Simulations Explained

31:15 Monte Carlo Simulations Explained

32:01 Applications of Monte Carlo Simulations

33:34 Introduction to AI and Reinforcement Learning

35:25 Reinforcement Learning in Finance

39:38 The Power of Python in Finance

42:23 Challenges in Measuring Returns

1:01:35 Conclusion and Final Thoughts

Understanding LLMOps: Differentiating from MLOps with Abi Aryan

Join Miko Pawlikowski on this episode of HockeyStick as he interviews Abi Aryan, a leading expert and author on Large Language Model Operations (LLMOps), to distinguish it from Machine Learning Operations (MLOps) and Machine Learning Engineering (MLE). Abi delves into the challenges and unique requirements of managing generative models in production, discusses the evolution and future of LLMOps, and shares insights into her upcoming book, 'LLMOps: Managing Large Language Models in Production.' Gain understanding on safety, scalability, robustness, and the lifecycle of LLMs, and learn practical steps to effectively deploy and monitor these advanced models.

00:00 Introduction

1:11 Generative vs. Discriminative Models

1:58 Challenges in LLMOps

2:12 The Shift to Task-Agnostic Software

2:50 Fine-Tuning and Prompt Engineering

4:37 The Origin of LLMOps

13:20 Safety, Scalability, and Robustness in LLMOps

29:40 Dynamic Model Adaptation

30:37 Challenges of Static Models

31:42 Improving Model Performance

32:20 Introducing a New Framework

34:06 Lifecycle of an LLM in Production

35:29 Data Engineering and Evaluation

37:06 Orchestration and Security

47:51 Future Predictions and Concerns

48:46 Impact on Jobs and Society

55:06 Risks and Ethical Considerations

59:11 Industry Trends and Monopolies

01:00:52 Conclusion and Contact Information

AI Impact on Software Testing: Expert Insights with Mark Winteringham

Get Mark's book 20% OFF with code hockeystick24 here: https://mng.bz/oeWD

In this episode of Hockey Stick, host Miko Pawlikowski welcomes Mark Winteringham, author of 'AI Assisted Testing,' to discuss the impact of generative AI on software testing.

They explore the efficacy of AI in writing tests, the future of software testing jobs, and the diverse roles within the testing profession. Mark provides his insights and experiences from 15 years in the industry, shares the concept of exploratory testing, and discusses the practical applications and limitations of AI tools in the testing landscape.

Key takeaways include the importance of empathy, critical thinking, and collaboration in testing, as well as how to effectively use AI tools for specific tasks. Tune in for an in-depth conversation on the evolving world of software testing.

00:00 Introduction to AI in Software Testing

00:17 Meet Mark Winteringham: A Journey into Software Testing

00:46 The Role and Daily Life of a Software Tester

14:01 Exploring the Impact of AI on Software Testing

17:35 Generative AI: Opportunities and Challenges

20:53 Practical Use Cases for AI in Testing

39:14 The Future of AI in Software Testing

42:02 Conclusion and Final Thoughts

The Essentials of MLOps: With Eric Riddoch

Join Miko Pawlikowski as he dives into the world of MLOps with Eric Riddoch, a machine learning platform engineer and MLOps practitioner. In this episode, they discuss the differences between MLOps, DevOps, and platform engineering, tools and practices in MLOps, as well as Eric's journey into the field from studying applied math to becoming an MLOps expert. They explore automated workflows, experiment tracking, model serving, and monitoring, while considering the evolving landscape of MLOps and the challenges of integrating various tools. Tune in for an in-depth look at the technical and non-technical aspects of MLOps, and learn why this field is critical and exciting.

00:00 Introduction to MLOps

01:20 Eric Riddoch's Journey into MLOps

08:12 The Emergence of MLOps

10:23 Comparing MLOps and DevOps

10:53 Challenges in MLOps

21:15 Tools and MLOps Maturity

25:57 Building an ML Platform with Orchestrators

26:35 Experiment Tracking and Model Performance

27:08 ML Flow and Alternatives

29:18 Serving Models with BentoML

31:49 Challenges with SageMaker and GPU Quotas

32:54 Monitoring Tools and Their Limitations

36:48 The PyTorch vs TensorFlow Debate

42:41 Challenges in MLOps Roles and Leadership

50:42 Advice for Aspiring MLOps Engineers