In 2020, Sara Hooker published "The Hardware Lottery", introducing an idea that has won high relevance today with AI evaluation: the best research is often what runs the fastest on currently available hardware. Her thesis is highly relevant as scaling returns slow down, and potential manipulation in benchmarks arises. In this episode of Kaggle Conversations, Meg Risdal sits down with Sara Hooker, CEO and co-founder of Adaption Labs, former VP of Research at Cohere, and member of Kaggle's Research Advisory Board. In this conversation, they cover: • Why the hardware lottery has intensified since 2020 • What the "leaderboard illusion" reveals about manipulation in AI evals • Why scaling is hitting diminishing returns and the paradigms that replace it • How an efficient stack could put research back outside frontier labs • What Adaption Labs’ Uncharted Data Challenge on Kaggle surfaced, including a submission of 129 datasets • The one idea Sara calls the most underrated in AI right now Read the “Hardware Lottery” paper: https://arxiv.org/abs/2009.06489v2 Subscribe for more Kaggle Conversations: https://www.youtube.com/c/kaggle Chapters 0:00 Why community drives frontier progress 0:24 Meg and Sara’s meeting in 2017 and the early DeepMind era 2:47 The through line: problem-driven research 5:28 The Aya project and building an ecosystem 8:44 The hardware lottery, explained 11:26 Why the hardware lottery has intensified since 2020 12:51 Deconstructing the “leaderboard illusion” 14:47 Shifting incentives in the AI research community 15:41 Structuring a fair leaderboard 17:01 The power of crowdsourced verification in Kaggle competitions 18:24 The diminishing returns of the scaling era 21:15 Investing in efficiency beyond scale 23:33 Adaption Labs and continuous learning 26:16 The potential obsolescence of prompt engineering 27:15 The Uncharted Data Challenge 30:21 How efficiency increases interest 31:14 Aligning your focus with functionality 33:04 Hiring globally and the talent thesis 34:46 The most underrated idea in AI right now About Kaggle: Kaggle’s global community of practitioners, researchers, and enthusiasts collaborate to shape the frontier of AI. Through AI competitions, benchmarks, agentic evaluation, Kaggle serves as both the engine and proving ground for community-led innovation. Follow Kaggle online 🌐 Visit the WEBSITE: https://www.kaggle.com ✍️ Check out our BLOG: https://www.kaggle.com/blog 🐦 Follow Kaggle on X: https://x.com/kaggle 🔗 Connect with us on LINKEDIN: https://www.linkedin.com/company/kaggle 🎮 Join us on the Kaggle Discord server: http://discord.gg/kaggle 🎥 Subscribe to our YouTube channel: https://www.youtube.com/@kaggle

In this episode of Kaggle Conversations, Meg Risdal, Product Lead at Kaggle, and Walter Reade, Technical Lead for Kaggle Competitions, sit down with Alex Shaw, Member of Technical Staff at the Laude Institute and co-creator of Terminal-Bench and Harbor. Alex left a stable job at Google after a phone call about a friend's $1 million idea: a benchmark competition designed so nobody could cheat. That idea became the Konwinski Prize, one of the most ambitious attempts yet to measure what AI coding agents can actually do. As coding agents improve and benchmark scores continue to climb, Alex has become increasingly focused on a difficult question: how do you know if progress is real? Through projects like Terminal-Bench, Harbor, and the Konwinski Prize, he's helping build a new generation of evaluations designed to withstand gaming, saturation, and shortcuts. In this conversation, they cover: • Why building a competition nobody can cheat is so difficult • What the Konwinski Prize revealed about the true state of coding agents • How Terminal-Bench and Harbor came together • Why pass-fail evaluations keep leaderboards meaningful • The difference between model capability and scaffolding • Why Alex believes the future of benchmarking is everyone building their own Alex is part of a growing movement questioning how AI progress is measured. This conversation explores what happens when benchmark scores stop being enough, and why the next generation of evaluation may look very different from the last. Subscribe for more Kaggle Conversations. Chapters 0:00 Cold open 0:31 Introductions 0:59 Alex Shaw and Walter Reade’s early connection 1:27 The defining career advice that led Alex into machine learning 1:57 Internships at Apple and Google 2:25 Leaving a Google project unfinished, and why it was the right move 3:21 How Alex's path crossed with Kaggle 3:49 Andy Konwinski and the Origins of the K Prize, a contamination-free SWE-Bench 4:44 SWE-Bench, and why it mattered 5:37 The challenge of building a competition nobody can cheat 6:36 How Kaggle shaped the competition design 7:05 What the K Prize revealed about coding agents 8:30 Harbor and accelerating benchmarks creation 9:00 The origins of Terminal-Bench 10:27 What gap Terminal-Bench fills 11:24 Why pass-fail keeps a leaderboard meaningful 11:54 Nerd-sniping friends into building evals 13:14 Designing benchmarks to resist model saturation 14:07 Scaffolding versus model capability 15:04 Why Alex Shaw built Harbor 16:33 Harbor format, framework, and registry 17:00 What the community built with it 17:58 The value of a standard 19:21 The Laude Institute and the bet on Andy Konwinski 21:15 Slingshots and moonshots 22:41 Connecting slingshots to Kaggle competitions 23:37 The AI benchmark Alex Shaw would build with a magic wand 24:50 Terminal-Bench 3 and getting involved 25:20 Close About Kaggle: Kaggle’s global community of practitioners, researchers, and enthusiasts collaborate to shape the frontier of AI. Through AI competitions, benchmarks, agentic evaluation, Kaggle serves as both the engine and proving ground for community-led innovation. Follow Kaggle online 🌐 Visit the WEBSITE: https://www.kaggle.com ✍️ Check out our BLOG: https://www.kaggle.com/blog 🐦 Follow Kaggle on TWITTER: https://twitter.com/kaggle 🔗 Connect with us on LINKEDIN: https://www.linkedin.com/company/kaggle 🎮 Join us on the Kaggle Discord server: http://discord.gg/kaggle 🎥 Subscribe to our YouTube channel: https://www.youtube.com/@kaggle

We’ve reached the last day’s assignment! 🎉 All the info about the course will be shared here: https://www.kaggle.com/competitions/5-day-ai-agents-intensive-vibecoding-course-with-google/discussion?sort=hotness Complete Unit 5 - “Spec-Driven Production Grade Development in the Age of Vibe Coding”: Listen to the summary podcast episode for this unit. https://www.youtube.com/watch?v=VSRdL4wlbLY To complement the podcast, read the “Spec-Driven Production Grade Development in the Age of Vibe Coding” whitepaper. https://www.kaggle.com/whitepaper-spec-driven-production-grade-development-in-the-age-of-vibe-coding Complete these codelabs: [Optional] Deploy and host your AI agents on Google Cloud https://codelabs.developers.google.com/enterprise-cloud-scale-deploying-the-expense-agent-to-agent-runtime-on-google-cloud#0 [Optional] Build a front-end web app and link it to your cloud-hosted AI agent https://codelabs.developers.google.com/vibecode-frontend-with-antigravity#0 🎮 Join us and other participants on Kaggle’s Discord server: http://discord.gg/kaggle 🔗 Resources & Links: Gemma 4: https://deepmind.google/models/gemma/gemma-4/ Siemens: https://cloud.google.com/blog/products/ai-machine-learning/how-siemens-sliced-the-elephant-modernizing-legacy-code-with-agentic-workflows/

All the info about the course will be shared here: https://www.kaggle.com/competitions/5-day-ai-agents-intensive-vibecoding-course-with-google/discussion?sort=hotness Complete Unit 4 - “Vibe Coding Agent Security and Evaluation”: Listen to the summary podcast episode for this unit. https://www.youtube.com/watch?v=Ddz1b8CYPvg To complement the podcast, read the Vibe Coding Agent Security and Evaluation whitepaper. https://www.kaggle.com/whitepaper-vibe-coding-agent-security-and-evaluation Complete these codelabs: Build an expense-approval agent with human-in-the-loop triage and local evaluations with ADK, Agents CLI and Antigravity https://codelabs.developers.google.com/vibecode-ambient-expense-agent#0 Write Secure AI Code: Automated Threat Scans, Safety Guards, and Security Testing https://codelabs.developers.google.com/secure-agentic-coding#0 🎮 Join us and other participants on Kaggle’s Discord server: http://discord.gg/kaggle

All the info about the course will be shared here: https://www.kaggle.com/competitions/5-day-ai-agents-intensive-vibecoding-course-with-google/discussion?sort=hotness Complete Unit 3 - “Agent Skills”: 1. Listen to the summary podcast episode for this unit. https://www.youtube.com/watch?v=uYURYHhpmKc 2. To complement the podcast, read the “Agent Skills” whitepaper. https://www.kaggle.com/whitepaper-agent-skills 3. Complete these codelabs on Kaggle: - Explore how Skills work in Antigravity https://codelabs.developers.google.com/getting-started-with-antigravity-skills?hl=en#4 - Build agents in Antigravity with Agents CLI and ADK https://codelabs.developers.google.com/agents-cli-adk-lifecycle#0 🎮 Join us and other participants on Kaggle’s Discord server: http://discord.gg/kaggle

All the info about the course will be shared here: https://www.kaggle.com/competitions/5-day-ai-agents-intensive-vibecoding-course-with-google/discussion?sort=hotness Day 2: Agent Tools & Interoperability 1. Listen to the summary podcast episode for this unit. https://www.youtube.com/watch?v=GjjKXqxFTOY 2. To complement the podcast, read the “Agent Tools & Interoperability” whitepaper. https://www.kaggle.com/whitepaper-agent-tools-and-interoperability 3. Complete these codelabs: - Get started with Antigravity CLI https://codelabs.developers.google.com/antigravity-cli-hands-on#0 - Explore Google Developer Knowledge MCP server in Google Antigravity https://codelabs.developers.google.com/developer-knowledge-mcp-antigravity#0 🎮 Join us and other participants on Kaggle’s Discord server: http://discord.gg/kaggle 🔗 Resources & Links: Google Managed MCP Servers Announcement:https://cloud.google.com/blog/products/ai-machine-learning/google-managed-mcp-servers-are-available-for-everyone?utm_campaign=CDR_0xf9030db1_default_b524668347&utm_medium=external&utm_source=blog Supported Google MCP Products (Docs):https://docs.cloud.google.com/mcp/supported-products?utm_campaign=CDR_0xf9030db1_default_b524668347&utm_medium=external&utm_source=blog Google MCP GitHub Repo: https://github.com/google/mcp Codelab - Build an ADK Agent with Google MCPs:https://codelabs.developers.google.com/next26/build-adk-agent-google-mcps?utm_campaign=CDR_0xf9030db1_default_b524668347&utm_medium=external&utm_source=blog#0

All the info about the course will be shared here: https://www.kaggle.com/competitions/5-day-ai-agents-intensive-vibecoding-course-with-google/discussion?sort=hotness Day 1: Introduction to Agents Complete the Unit 1 – “Introduction to Agents”: 1. Listen to the summary podcast episode for this unit – https://youtu.be/cbzmr7vt4XA 2. To complement the podcast, read the “The New SDLC With Vibe Coding ” whitepaper: https://www.kaggle.com/whitepaper-the-new-SDLC-with-vibe-coding 3. Complete these codelabs on Kaggle: a. Get started with Antigravity 2.0 and IDE:p https://codelabs.developers.google.com/getting-started-google-antigravity#0 b. Build a Web Application in AI Studio and Deploy to Cloud Ru:p https://codelabs.developers.google.com/deploy-from-aistudio-to-run?hl=en#0 🎮 Join us and other participants on Kaggle’s Discord server: http://discord.gg/kaggle Read the DeepMind paper on AlphaEvolve: https://deepmind.google/blog/alphaevolve-a-gemini-powered-coding-agent-for-designing-advanced-algorithms/ Learn about Long Running agents in this episode of Google cloud’s agent factory: https://www.youtube.com/watch?v=VGpfnbr7rso Start building stateful AI agents with the Agent Development Kit (ADK):https://developers.googleblog.com/build-long-running-ai-agents-that-pause-resume-and-never-lose-context-with-adk/?utm_campaign=CDR_0xf9030db1_default_b524246263&utm_medium=external&utm_source=youtube Check out the open-source Google Skills project on GitHub: https://github.com/google/skills Read the guide on accelerating your TensorFlow to JAX migration:https://cloud.google.com/blog/topics/developers-practitioners/6x-faster-migration-from-tensorflow-to-jax?utm_campaign=CDR_0xf9030db1_default_b524246263&utm_medium=external&utm_source=youtube

Nick Kang, Product Manager on Kaggle Benchmarks, walks through how to build, run, and push an AI evaluation task in your own local development environment. He installs the write-kaggle-benchmarks from GitHub, initializes the environment, and builds a colorblind image test from scratch, asserting the correct output, validating it locally, and pushing it to Kaggle to run across four models: Gemini 3 Flash Preview, Gemini 3.5 Flash, GPT 5.5, and Opus 4.7. Results come back with pass/fail, latency, cost, and token counts. All visualized directly in the CLI and agent panel. 👉 Install the write-kaggle-benchmarks skill: https://github.com/Kaggle/kaggle-skills/tree/main/write-kaggle-benchmarks 👉 Get started on: https://www.kaggle.com/benchmarks About Kaggle: Kaggle’s global community of practitioners, researchers, and enthusiasts collaborate to shape the frontier of AI. Through AI competitions, benchmarks, agentic evaluation, Kaggle serves as both the engine and proving ground for community-led innovation. Follow Kaggle online 🌐 Visit the WEBSITE: https://www.kaggle.com ✍️ Check out our BLOG: https://www.kaggle.com/blog 🐦 Follow Kaggle on TWITTER: https://twitter.com/kaggle 🔗 Connect with us on LINKEDIN: https://www.linkedin.com/company/kaggle 🎮 Join us on the Kaggle Discord server: http://discord.gg/kaggle 🎥 Subscribe to our YouTube channel: https://www.youtube.com/@kaggle

Stay Updated with Kaggle Benchmark Notifications! We’ve introduced three new ways to track AI progress on Kaggle. Whether you're a benchmark owner or a follower, you can now get real-time alerts via web and email. About Kaggle: Kaggle’s global community of practitioners, researchers, and enthusiasts collaborate to shape the frontier of AI. Through AI competitions, benchmarks, agentic evaluation, Kaggle serves as both the engine and proving ground for community-led innovation. Follow Kaggle online 🌐 Visit the WEBSITE: https://www.kaggle.com ✍️ Check out our BLOG: https://www.kaggle.com/blog 🐦 Follow Kaggle on TWITTER: https://twitter.com/kaggle 🔗 Connect with us on LINKEDIN: https://www.linkedin.com/company/kaggle 🎮 Join us on the Kaggle Discord server: http://discord.gg/kaggle 🎥 Subscribe to our YouTube channel: https://www.youtube.com/@kaggle

Welcome to Kaggle's 5-Day AI Agents Intensive course with Google! This video is your essential, quick guide to navigating and using the Kaggle Notebooks environment for the intensive. What You'll Learn: Notebook Essentials - Whether you're new to Kaggle or need a quick refresher, this video covers all the basics you need to start coding effectively: - Understand notebooks as your interactive coding environment - Learn about code cells (for writing and executing code in Python) and markdown cells (for documentation) - Master how to edit cells, how to run cells, and the importance of the order of running cells in notebooks - See how to share notebooks with others for collaboration - How to add API keys via Kaggle Secrets so you don't save API keys as plaintext 🎮 Join us and other participants on Kaggle Discord server: http://discord.gg/kaggle

Read the whitepaper here: https://www.kaggle.com/whitepaper-introduction-to-agents Learn more about the 5-Day AI Agents Intensive: https://rsvp.withgoogle.com/events/google-ai-agents-intensive_2025 Introduction: Artificial intelligence is changing. For years, the focus has been on models that excel at passive, discrete tasks: answering a question, translating text, or generating an image from a prompt. This paradigm, while powerful, requires constant human direction for every step. We're now seeing a paradigm shift, moving from AI that just predicts or creates content to a new class of software capable of autonomous problem-solving and task execution. This new frontier is built around AI agents. An agent is not simply an AI model in a static workflow; it's a complete application, making plans and taking actions to achieve goals. It combines a Language Model's (LM) ability to reason with the practical ability to act, allowing it to handle complex, multi-step tasks that a model alone cannot. The critical capability is that agents can work on their own, figuring out the next steps needed to reach a goal without a person guiding them at every turn. 👉 Learn more about ADK here: https://google.github.io/adk-docs/ 🎮 Join us and other participants on Kaggle Discord server: http://discord.gg/kaggle

Read the whitepaper here: https://www.kaggle.com/whitepaper-agent-tools-and-interoperability-with-mcp Learn more about the 5-Day AI Agents Intensive: https://rsvp.withgoogle.com/events/google-ai-agents-intensive_2025 Introduction: In this whitepaper we talk first about the nature of tools used by foundation models: what they are and how to use them. We give some best practices and guidelines for designing effective tools and using them effectively. We then look at the Model Context Protocol, talking about its basic components and some of the challenges and risks it entails. Finally, we take a deeper look at the security challenges posed by MCP as it is introduced in an enterprise environment and connected to high-value external systems. 👉 Learn more about ADK here: https://google.github.io/adk-docs/ 🎮 Join us and other participants on Kaggle Discord server: http://discord.gg/kaggle

Read the whitepaper here: https://www.kaggle.com/whitepaper-context-engineering-sessions-and-memory Learn more about the 5-Day AI Agents Intensive: https://rsvp.withgoogle.com/events/google-ai-agents-intensive_2025 Introduction: This whitepaper explores the critical role of Sessions and Memory in building stateful, intelligent LLM agents to empower developers to create more powerful, personalized, and persistent AI experiences. To enable Large Language Models (LLMs) to remember, learn, and personalize interactions, developers must dynamically assemble and manage information within their context window—a process known as Context Engineering. 👉 Learn more about ADK here: https://google.github.io/adk-docs/ 🎮 Join us and other participants on Kaggle Discord server: http://discord.gg/kaggle

Read the whitepaper here: https://www.kaggle.com/whitepaper-agent-quality Learn more about the 5-Day AI Agents Intensive: https://rsvp.withgoogle.com/events/google-ai-agents-intensive_2025 Introduction: This is a practical guide from evaluation to observability. We are at the dawn of the agentic era. The transition from predictable, instruction-based tools to autonomous, goal-oriented AI agents presents one of the most profound shifts in software engineering in decades. While these agents unlock incredible capabilities, their inherent non-determinism makes them unpredictable and shatters our traditional models of quality assurance. This whitepaper serves as a practical guide to this new reality, founded on a simple but radical principle: agent quality is an architectural pillar, not a final testing phase. 👉 Learn more about ADK here: https://google.github.io/adk-docs/ 🎮 Join us and other participants on Kaggle Discord server: http://discord.gg/kaggle

Read the whitepaper here: https://www.kaggle.com/whitepaper-prototype-to-production Learn more about the 5-Day AI Agents Intensive: https://rsvp.withgoogle.com/events/google-ai-agents-intensive_2025 Introduction: This whitepaper provides a comprehensive technical guide to the operational life cycle of AI agents, focusing on deployment, scaling, and productionizing. Building on Day 4's coverage of evaluation and observability, this guide emphasizes how to build the necessary trust to move agents into production through robust CI/CD pipelines and scalable infrastructure. It explores the challenges of transitioning agent-based systems from prototypes to enterprise- grade solutions, with special attention to Agent2Agent (A2A) interoperability. This guide offers practical insights for AI/ML engineers, DevOps professionals, and system architects. 👉 Learn more about ADK here: https://google.github.io/adk-docs/ 🎮 Join us and other participants on Kaggle Discord server: http://discord.gg/kaggle

Join the Measuring Progress Toward AGI - Cognitive Abilities hackathon team for a technical breakdown of the "Measuring Progress Toward AGI: A Cognitive Framework" paper and its application to your hackathon tasks. Agenda: 20-Min Deep Dive: A walkthrough of the research paper, cognitive faculty examples, and exactly what the judges are looking for in a winning benchmark. 20-Min Live AMA: Your chance to ask the authors anything about the framework, task design, or scoring. The Panel: Ryan Burnell, Staff Research Scientist, Google DeepMind (https://x.com/DrRyanBurnell) Oran Kelly, Product Manager, Google DeepMind (https://www.linkedin.com/in/oran-kelly/) Nick Kang Product Manager, Kaggle Benchmarks (https://x.com/nick_kango) Enter the Hackathon: https://www.kaggle.com/competitions/kaggle-measuring-agi The Paper: https://storage.googleapis.com/deepmind-media/DeepMind.com/Blog/measuring-progress-toward-agi/measuring-progress-toward-agi-a-cognitive-framework.pdf SUBSCRIBE: https://www.youtube.com/c/kaggle?sub_confirmation=1&utm_medium=youtube&utm_source=channel&utm_campaign=yt-sub About Kaggle: Kaggle’s global community of practitioners, researchers, and enthusiasts collaborate to shape the frontier of AI. Through AI competitions, benchmarks, agentic evaluation, Kaggle serves as both the engine and proving ground for community-led innovation. Follow Kaggle online: Visit the WEBSITE: http://www.kaggle.com/?utm_medium=youtube&utm_source=channel&utm_campaign=yt-kg Like Kaggle on FACEBOOK: http://www.facebook.com/kaggle?utm_medium=youtube&utm_source=channel&utm_campaign=yt-fb Follow Kaggle on TWITTER: http://twitter.com/kaggle?utm_medium=youtube&utm_source=channel&utm_campaign=yt-tw Check out our BLOG: http://blog.kaggle.com/?utm_medium=youtube&utm_source=channel&utm_campaign=yt-blog Connect with us on LINKEDIN: http://www.linkedin.com/company/kaggle?utm_medium=youtube&utm_source=channel&utm_campaign=yt-lkn Advance your data science skills: Take our free online courses: http://www.kaggle.com/learn/overview?utm_medium=youtube&utm_source=channel&utm_campaign=yt-learn Get started with Kaggle Kernels: http://www.kaggle.com/docs/kernels?utm_medium=youtube&utm_source=channel&utm_campaign=yt-krnl Download clean datasets from Kaggle: http://www.kaggle.com/docs/datasets?utm_medium=youtube&utm_source=channel&utm_campaign=yt-datast Sign up for a Kaggle Competition: http://www.kaggle.com/docs/competitions?utm_medium=youtube&utm_source=channel&utm_campaign=yt-comps Explore the Kaggle Public API: http://www.kaggle.com/docs/api?utm_medium=youtube&utm_source=channel&utm_campaign=yt-docs Kaggle https://www.youtube.com/c/kaggle

Join the Measuring Progress Toward AGI - Cognitive Abilities hackathon team for a technical breakdown of the "Measuring Progress Toward AGI: A Cognitive Framework" paper and its application to your hackathon tasks. Agenda: 20-Min Deep Dive: A walkthrough of the research paper, cognitive faculty examples, and exactly what the judges are looking for in a winning benchmark. 20-Min Live AMA: Your chance to ask the authors anything about the framework, task design, or scoring. The Panel: Ryan Burnell, Staff Research Scientist, Google DeepMind (https://x.com/DrRyanBurnell) Oran Kelly, Product Manager, Google DeepMind (https://www.linkedin.com/in/oran-kelly/) Nick Kang Product Manager, Kaggle Benchmarks (https://x.com/nick_kango) Enter the Hackathon: https://www.kaggle.com/competitions/kaggle-measuring-agi The Paper: https://storage.googleapis.com/deepmind-media/DeepMind.com/Blog/measuring-progress-toward-agi/measuring-progress-toward-agi-a-cognitive-framework.pdf SUBSCRIBE: https://www.youtube.com/c/kaggle?sub_confirmation=1&utm_medium=youtube&utm_source=channel&utm_campaign=yt-sub About Kaggle: Kaggle is the world's largest community of data scientists. Join us to compete, collaborate, learn, and do your data science work. Kaggle's platform is the fastest way to get started on a new data science project. Spin up a Jupyter notebook with a single click. Build with our huge repository of free code and data. Stumped? Ask the friendly Kaggle community for help. Follow Kaggle online: Visit the WEBSITE: http://www.kaggle.com/?utm_medium=youtube&utm_source=channel&utm_campaign=yt-kg Like Kaggle on FACEBOOK: http://www.facebook.com/kaggle?utm_medium=youtube&utm_source=channel&utm_campaign=yt-fb Follow Kaggle on TWITTER: http://twitter.com/kaggle?utm_medium=youtube&utm_source=channel&utm_campaign=yt-tw Check out our BLOG: http://blog.kaggle.com/?utm_medium=youtube&utm_source=channel&utm_campaign=yt-blog Connect with us on LINKEDIN: http://www.linkedin.com/company/kaggle?utm_medium=youtube&utm_source=channel&utm_campaign=yt-lkn Advance your data science skills: Take our free online courses: http://www.kaggle.com/learn/overview?utm_medium=youtube&utm_source=channel&utm_campaign=yt-learn Get started with Kaggle Kernels: http://www.kaggle.com/docs/kernels?utm_medium=youtube&utm_source=channel&utm_campaign=yt-krnl Download clean datasets from Kaggle: http://www.kaggle.com/docs/datasets?utm_medium=youtube&utm_source=channel&utm_campaign=yt-datast Sign up for a Kaggle Competition: http://www.kaggle.com/docs/competitions?utm_medium=youtube&utm_source=channel&utm_campaign=yt-comps Explore the Kaggle Public API: http://www.kaggle.com/docs/api?utm_medium=youtube&utm_source=channel&utm_campaign=yt-docs Kaggle https://www.youtube.com/c/kaggle