Shakudo
Big Data, small talk
Are you ready to dive deep into the world of artificial intelligence and data science? In this Podcast, some of the brightest minds in the industry cover a range of topics relevant to data scientists and professionals working in AI, from machine learning algorithms to big data analysis. Whether you're just starting in data science or are a seasoned pro, this show is for you!
Where to listen?
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Episodes
EP 14 - Best Open Source Tools for Data Engineering 14.08.2023 56:17
In this episode we brought Dipankar Mazumdar and Alex Merced from Dremio to discuss all about the best open source tools for modern data engineering, data lakehouse functionality, and give a sneak peek into their soon-to-be-released book, "Apache Iceberg: The Definitive Guide”
EP 13 - LLMs: Building Faster, Cheaper and More Effectively 14.07.2023 56:50
In this episode, we'll talk about how LLMs have evolved, the strategies for using them effectively, and how to pick the right model for your project. We'll also touch on the difference between open-source and proprietary LLMs, and the importance of data privacy with our experts Shubham Saboo, Sai Kalyan Siddanatham, Runzhou Li, and Mayo Oshin. References mentioned: https://arxiv.org/abs/2305.14314...
EP 12 - The Least You MUST Know About Docker 14.06.2023 53:55
From the creation of Docker images to the orchestration of containers, we break down the basics to give you a firm foundation. This episode serves as your gateway to Docker, providing an easily digestible guide to the essentials. Tune in to discover the least you must know about Docker with Francesco Ciulla, Shelley Benhoff, Pradumna Saraf and Mohammad-Ali A'RÂBI.
EP 11 - Implementing AI as Business Solutions 23.05.2023 56:57
This episode demystifies the ever-evolving AI landscape and provides practical insights for businesses ready to step into the future. We'll explore what AI truly means in the business realm, discuss real-world examples of companies successfully leveraging AI, and offer strategies to implement and adapt to these new technologies. With: Stella Wu, Greg Kamradt, and Travis Fischer.
EP 10 - Large Language Models in Production 24.04.2023 56:07
Let's explore the challenges of implementing large language models (LLMs) and the ethical considerations that come into play. Join our speakers as they delve into the world of LLMs and explore their impact on privacy, open-source development, and ethics. Featuring Christine Yuen, Abi Aryan, and Aurimas Griciūnas.
EP 9 - Explaining Distributed Systems Like I'm 5 10.04.2023 52:37
What are the foundations of Distributed Systems? Let's demystify this complex world, making it truly accessible for everyone. Join our panel with Sage Elliot, Kevin Kho, Stella Wu, and Nicolas Perez, breaking down intricate ideas into clear, easy-to-understand explanations.
EP 8 - Data Science 101: Tools and Tips for Success 10.04.2023 49:27
Ready to level up your data science skills from the very beginning? Let's unlock the secrets of data analysis, visualization, and interpretation with the guidance of our expert panel. Featuring Jessica Temporal, Filipe Mesquita, Harpreet Sahota, and Michael Galarnyk. You'll be guided through the fundamentals of data science, helping you build a strong foundation while uncovering essential tools, s...
EP 7 - How to Build a Mordern Web Application 10.04.2023 1:04:43
Get ready for an insightful talk on building modern web applications. Our panel of experts, Felippe Regazio, Charlie Greenman, Rohit Ghumare, Ceora Ford, and Daniel Reis, will reveal the most exciting examples, latest tools, frameworks, and best practices that will supercharge and modernize your web development journey.
EP 6 - What is MLOps? 10.04.2023 51:15
Discover the core principles, best practices, and state-of-the-art tools that facilitate seamless collaboration between data scientists and engineers. Let's uncover how MLOps empowers teams to expedite innovation, enhance model reliability, and uphold top-notch machine learning solutions in real-world applications. With Ahirton Lopes, Fatos Ismali, and Mikiko Bazeley.
EP 5 - Where Should I Run My App? Simplicity vs Flexibility 10.04.2023 58:30
This is a journey to discover the ideal environment for running your app, as we compare simplicity and flexibility in various deployment scenarios. Our expert panelists Pradumna Saraf, Aditya Oberai, Kelvin Omereshone, and Devon Hockley are providing insights on balancing ease of use with customization options. Here are their experiences and strategies on how to make informed decisions on app host...
EP 4 - How to Build Efficient Machine-Learning Pipelines 10.04.2023 1:00:30
Let's dive into the world of efficient ML pipelines as we discuss best practices, covering crucial aspects such as data preprocessing, feature engineering, model training, and evaluation. Join our expert panelists Avi Kumar, Marcel Ribeiro, and Gustavo Martins as they explore popular tools like SciKit Learn, NextFlow, and Spark to optimize workflows and ensure robust machine learning solutions. Le...
EP 2 - Solving the Complexity of Moving Data Science to Production 30.03.2023 1:28:01
Let's explore key considerations, including model deployment, monitoring, and ongoing maintenance, to ensure smooth and efficient integration of ML models into real-world applications. With Pau Labarta, Mikiko Bazeley, Chanin Nantasenamat and Tawanda Nyahuye.
EP 1 - The Challenges of Putting and Keeping ML Models in Production 20.12.2022 1:01:43
From model deployment to monitoring and maintenance, in this episode, experts in the field share their war stories and offer practical advice on how to overcome the obstacles that often arise when deploying ML models. With Stella Wu, Harpreet Sahota, Michael Galarnyk and Kirsten Lum.
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