Machine Learning is growing in leaps and bounds both in capability and adoption. Listen to our experts discuss the ideas and fundamentals needed to succeed as a Machine Learning Engineer.
Similar Podcasts
Flutter 101 Podcast
Weekly podcast focusing on software development with Flutter and Dart. Hosted by Vince Varga.
Views on Vue
Vue is a growing front-end framework for web developments. Hear experts cover technologies and movements within the Vue community by talking to members of the open source and development community.
React Round Up
Stay current on the latest innovations and technologies in the React community by listening to our panel of React and Web Development Experts.
Combating Burnout in Machine Learning: Strategies for Balance and Collaboration - ML 178
In this episode, Ben and Michael explore burnout, particularly in machine learning and data science. They highlight that burnout stems from exhaustion, cynicism, and inefficiency and can be caused by repetitive tasks, overwhelming workloads, or being in the wrong role. They also tackle strategies to combat burnout, including collaborating with others, mentoring, shifting focus between tasks, and hiring more people to distribute the workload. A key takeaway is the importance of knowledge sharing and not hoarding tasks for job security, as this can lead to burnout and inefficiency. They also discuss managing burnout and its components, particularly exhaustion, cynicism, and inefficiency, through personal experiences. Finally, they talk about how burnout can lead to inefficiency and physical manifestations, like a lack of motivation to engage in activities outside of work.Socials LinkedIn: Ben WilsonLinkedIn: Michael Berk Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.
The Nature of the World and AI with Rishal Hurbans - ML 177
Rishal Hurbans is the author of Grokking Artificial Intelligence Algorithms. He walks us through how to learn different Machine Learning algorithms. He also then walks us through the different types of algorithms based on different natural systems and processes.LinksKaggle: Your Machine Learning and Data Science CommunityRishal HurbansInktoberBook giveaway linkPicksChuck- Hero with a thousand faces by Joseph CampbellChuck- Masterbuilt smokerRishal-Learn something new everydayRishal- Building a StoryBrand by Donald MillerBecome a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.
Crafting Data Solutions: Shrinking Pie and Leveraging Insights for Optimal Data Learning - ML 176
In today’s episode, Michael and Ben are joined by industry expert Barzan Mozafari, the CEO and co-founder at Keebo. He delves deep into the evolving landscape of data learning and cloud optimization. They explore how understanding data distribution can lead to early detection of anomalies and how optimizing data workflows can result in significant cost savings and unintended business growth. Barzan sheds light on leveraging existing cloud technologies and the role of automated tools in enhancing system interactions, while Ben talks about the intricacies of platform migration and tech debt.They dig into the challenges and strategies for optimizing complex data pipelines, the economic pressures faced by data teams, and insights into innovation stemming from academic research. The conversation also covers the importance of maintaining customer trust without compromising data security and the iterative nature of both academic and industrial approaches to problem-solving. Join them as they navigate the intersection of technical debt, AI-driven optimization, and the dynamic collaboration between researchers and engineers, all aimed at driving continuous improvement and innovation in the world of data.So, gear up for an episode packed with insights on shrinking pie data learning, cloud costs, automated optimization tools, and much more. Let’s dive right in!SocialsLinkedIn: Barzan MozafariBecome a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.
Challenges and Solutions in Managing Code Security for ML Developers - ML 175
Today, join Michael and Ben as they delve into crucial topics surrounding code security and the safe execution of machine learning models. This episode focuses on preventing accidental key leaks in notebooks, creating secure environments for code execution, and the pros and cons of various isolation methods like VMs, containers, and micro VMs.They explore the challenges of evaluating and executing generated code, highlighting the risks of running arbitrary Python code and the importance of secure evaluation processes. Ben shares his experiences and best practices, emphasizing human evaluation and secure virtual environments to mitigate risks.The episode also includes an in-depth discussion on developing new projects with a focus on proper engineering procedures, and the sophisticated efforts behind Databricks' Genie service and MLflow's RunLLM. Finally, Ben and Michael explore the potential of fine-tuning machine learning models, creating high-quality datasets, and the complexities of managing code execution with AI.Tune in for all this and more as we navigate the secure pathways to responsible and effective machine learning development.SocialsLinkedIn: Michael BerkLinkedIn: Ben WilsonBecome a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.
Innovative Security Solutions for Developers - ML 174
They delve into the journeys and insights of distinguished leaders in the development world. In today's episode, Michael engages with Brian Vallelunga, the visionary CEO of Doppler. Brian shares his compelling journey from early tech innovations to leading multiple startups and eventually founding Doppler, a centralized cloud secret management tool.Brian emphasizes the importance of making security tools enticing for developers, comparing it to making vegetables taste like candy, to boost productivity. His team’s strategy revolves around seamless integration into developers’ workflows, featuring a VS Code extension and automatic syncing akin to Dropbox, enhancing efficiency and ease of use.They explore Doppler's competitive edge and how it partners with major cloud resource managers, making two-click integrations effortless. Brian also discusses their customer-centric development approach and the release of enterprise features like two-person approval and config inheritance, designed for complex organizational needs.Brian's entrepreneurial journey is marked by significant pivots driven by frustration and market demand, rather than strategic planning alone. He shares candid thoughts on the impact of founders and success, cautioning against the allure of celebrity status and emphasizing team contributions.Join them as they dive into insightful discussions on building developer-friendly security tools, the nuances of secret management, and Brian's perspectives on startup growth and innovation. Discover how Doppler is revolutionizing secret management, one integration at a time.SocialsLinkedIn: Brian VallelungaBecome a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.
Peer Review and Career Development - ML 173
In today's episode, Michael and Ben discuss peer review, specifically Michael's experiences. Michael explains his unconventional path, starting with advanced math as a child, then struggling with a math-heavy computer science program in college. He pivoted to environmental studies, focusing on side projects and extracurriculars. These projects led to his first job, and later to a role at a boxing streaming service (2B) with a rigorous peer review process. Ben asks about the importance of the peer review process, and Michael highlights its value in catching errors and ensuring code quality, especially when working under pressure. Moreover, Ben discusses the learning experience at different career stages, noting that junior developers learn from senior developers' code and feedback. Ben discusses the differences in peer review for different types of code changes. They discuss the importance of thorough review for critical code changes and many more!SocialsLinkedIn: Ben WilsonLinkedIn: Michael Berk Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.
Navigating Expertise Gaps - ML 172
In today's episode, Ben and Michael discuss how to handle situations involving individuals lacking expertise in machine learning projects. They explore scenarios where a team lacks expertise, considering approaches for consultants or team members. They discuss various personality types encountered in such situations, including those overly suspicious or resistant to change. Moreover, they discuss how to convince a boss that a proposed project is a bad idea, suggesting a structured approach with clear estimates, risk assessment, and alternative solutions. They emphasize the importance of honesty, transparency, and presenting options with clear pros and cons. The discussion then returns to the Gen AI time-series case study, suggesting a presentation of multiple options, including established algorithms and the Gen AI approach, to facilitate a data-driven decision.Finally, the episode addresses the scenario of a teammate being untrained about a system they built, suggesting a combination of direct but constructive feedback and a collaborative approach to identify the root cause of the issue.SocialsLinkedIn Ben WilsonLinkedIn Michael BerkBecome a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.
The Influence of Gen AI on Personalized Education and Curiosity - ML 171
In this episode, Michael and Ben dive deep into the intersection of education and technology with their insightful guest, Daniel Hiterer.Michael, a data engineering and machine learning expert, and Ben, an integrator of Gen AI tools, navigate through Danny's unique perspective on the impact of nurturing educational environments. Currently working at Cornell’s Studio entrepreneurship program, Danny brings a multidisciplinary background, combining history and instructional technology, and shares his vision for the future of learning.This episode explores the transformative power of nurture in education, the evolving role of Gen AI in fostering curiosity, and the challenges and opportunities in integrating AI into the learning process. Danny provides thought-provoking insights on emotional access points, curiosity-driven learning, and the delicate balance between educational goals and productivity tools.Listen in as they discuss personalized education, the promise of AI-assisted learning, and the future trajectory of superintelligence in education. Plus, hear personal anecdotes from Ben and Michael about their own learning journeys and the evolving landscape of curiosity and knowledge.SocialsLinkedIn: Daniel HitererBecome a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.
The Role of Open Source in Modern Development Practices - ML 170
Today, they dive deep into the fascinating intersection of open-source development and machine learning. Michael and Ben are joined by distinguished guest, Görkem Erkan, CTO and seasoned engineer at Jozu.Görkem shares his illustrious career journey from Nokia to Red Hat, his contributions to the Eclipse Foundation, and his current focus on MLOps. They explore his passion for open-source projects, the cultural and communication impacts on software design, and the unique challenges posed by integrating open-source frameworks with proprietary systems. Ben provides critical insights on the complexities of managing scalable backend services and the hurdles in translating SaaS offerings to open-source platforms.Tune in to learn about the innovative practices at Jozu, the role of open communication in team success, and the nuanced debate on maintaining separate proprietary and open-source codebases. This episode is packed with valuable lessons for developers, tech leaders, and anyone interested in the future of machine learning and open-source development. SocialsLinkedIn: Görkem Ercan Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.
AI-Powered Tools for Productivity with Artem Koren - ML 169
In this week's episode, Michael and Ben sit down with Artem Koren, Chief Product Officer at Sembly AI, to explore the future of AI integration in the workplace. We'll delve into Sembly AI's mission to accelerate team efficiency through powerful AI tools—imagine an Iron Man suit for your daily tasks. From proactive AI assisting with time-consuming tasks to ethical considerations in data privacy, this episode covers the cutting-edge developments and challenges in AI implementation.They also discuss the evolving landscape of workplace automation, the intricacies of data collection, and the balance between privacy and productivity. They also highlight Sembly's latest advancements like Semblian 2.0, a breakthrough in digital twin technology that promises to redefine meeting productivity. Join them for an in-depth conversation on AI's transformative potential, the ethical responsibilities it entails, and the practical impacts on the project. LinksSemblian 2.0SocialsLinkedIn: Artem KorenBecome a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.
The Impact of Generative AI on the Advertising Industry - ML 168
In today's episode, Michael is joined by Hikari Senju the Founder and CEO at Omneky. He starts by discussing how he built Omneky, an AI-Driven Marketing Platform. They dive into Hikari's approach to working with customers on brand strategy and content. They also talk about the increasing importance of brands in a digital, AI-driven world. Additionally, they tackle Hikari's perspective on how generative AI will impact the advertising industry. Tune in on how ML is Reshaping The Advertising Industry.SocialsLinkedIn: Hikari SenjuBecome a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.
Learning, Testing, and Mentorship: Building Autonomy and Confidence in Python Development - ML 167
Today, Ben and Michael dive into a compelling discussion on the intricate dance between challenges, feedback, mentorship, and growth in the field of software development. In this episode, Michael shares their journey of overcoming the pains of independent problem-solving before receiving effective guidance. As we explore their experiences with Ben, they uncover the vital importance of openness to feedback and the profound value of peer review in refining solutions.They delve into technical aspects, including Python's Pytest framework for unit tests and the delicate balance between complexity and simplicity in testing for maintainability and readability. Additionally, they touch on Michael's hands-on learning curve, tackling unfamiliar concepts such as RAG, embeddings, LLMs, and Git development, all while managing significant time constraints and social commitments.Moreover, Ben shares his mentorship philosophy, likening it to military training—pushing mentees to their limits without prior warning to foster resilience and self-improvement. They also discuss the importance of documentation, bug bashes, and the fine art of balancing integration and unit tests to ensure robust and thorough software.Join them as they explore the journey from initial struggle to increased autonomy and confidence, using real-world examples of testing gaps, code complexities, and the powerful impact of daily feedback. Whether you're a seasoned developer or just starting your tech career, this episode is packed with valuable insights to enhance your learning and development process. So, stay tuned and dive right in!Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.
Evaluating and Building AI Systems - ML 166
Michael Berk dives deep into the adventures of AI and machine learning with our special guest, Richmond Alake, a staff developer advocate at MongoDB. Richmond's journey from web development to AI was driven by a quest for excitement and new challenges. In this episode, he shares how he transitioned into the AI field, his passion for using writing as a learning tool, and the importance of continuous learning in evolving tech landscapes.They explore the intricacies of building and evaluating Retrieval-Augmented Generation (RAG) systems, the benefits of MongoDB's versatile database functionalities, and the pressing challenges in machine learning data collection and evaluation. Richmond also gives us a peek into MongoDB's advanced solutions for AI application development and how strategic data chunking can impact efficiency.Whether you're a budding AI enthusiast or an experienced developer looking to expand your horizons, this episode is packed with practical advice, career insights, and the latest trends in AI and machine learning. Stay tuned as we uncover how to navigate the complexity of RAG pipelines and the evolving landscape of generative AI. Let's get started!SocialsLinkedIn: Richmond AlakeBecome a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.
Demystifying AI Innovations - ML 165
Today, we have a special guest Abi Aryan, an accomplished founder of Abide AI and a seasoned expert in machine learning. Joining us are your hosts, Michael Berk and Ben Wilson, who bring a wealth of experience from Databricks.In this episode, Ben shares his journey navigating the intricacies of deep learning and the surprising effectiveness of simpler solutions over complex algorithms. Abi lends her insights to the balancing act between innovation and practicality in tech adoption, influenced by career stability and venture capital demands. They also explore Abi's passion for recommender systems and audio speech synthesis, and the potential these fields hold for e-commerce and inclusivity.Abi also gives us a glimpse into her research methodology, her approach to autonomous agents, and the challenges she faced with bias and imposter syndrome. As they dissect consulting strategies, experiment design, and the art of fostering a collaborative environment, this episode is packed with valuable lessons for any tech enthusiast.So, get ready to tune in, take notes, and be inspired by the fascinating stories and insights from our expert guest and hosts.SocialsAbi AryanLinkedIn: Abi AryanBecome a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.
Maintaining Backward Compatibility in Software Projects: Strategies from Industry Experts - ML 164
Today, host Michael Berk and Ben Wilson dive deep into the multifaceted world of software engineering and data science with their insightful guest, Sandy Ryza a lead engineer from Dagster Labs. In this episode, they explore a range of intriguing topics, from the impact of the broken windows theory on code quality to the delicate balance of maintaining backward compatibility in evolving software projects. Sandy talks about the challenges and learnings in transitioning from data science back to software engineering, including dependency management and designing for diverse use cases. They touch on the importance of clear naming conventions, tooling, and infrastructure enforcement to maintain high code quality. Plus, they discuss the intricate process of selecting and managing Python libraries, the satisfaction of refactoring old code, and the necessity of balancing new feature development with stability.Michael and Ben will guide us through these essential discussions, emphasizing the significance of user-centric API design and the benefits of open source software. They also get practical advice on navigating API changes and managing dependencies effectively, with real-world examples from Dagster, Spark Time Series, and the libraries Numba and Pydantic.Join them for an episode packed with valuable insights and strategies for becoming a top-end developer! Don’t forget to follow Sandy on Twitter and check out Dagster.io for more information on his work.SocialsLinkedIn: Sandy RyzaBecome a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.