DataTalks.Club

DataTalks.Club

DataTalks.Club - the place to talk about data!

  1. 5 NGÀY TRƯỚC

    Lessons from Two Decades of AI - Micheal Lanham

    In this episode, we talk with Michael Lanham, an AI and software innovator with over two decades of experience spanning game development, fintech, oil and gas, and agricultural tech. Michael shares his journey from building neural network-based games and evolutionary algorithms to writing influential books on AI agents and deep learning. He offers insights into the evolving AI landscape, practical uses of AI agents, and the future of generative AI in gaming and beyond.TIMECODES00:00 Micheal Lanham’s career journey and AI agent books05:45 Publishing journey: AR, Pokémon Go, sound design, and reinforcement learning10:00 Evolution of AI: evolutionary algorithms, deep learning, and agents13:33 Evolutionary algorithms in prompt engineering and LLMs18:13 AI agent books second edition and practical applications20:57 AI agent workflows: minimalism, task breakdown, and collaboration26:25 Collaboration and orchestration among AI agents31:24 Tools and reasoning servers for agent communication35:17 AI agents in game development and generative AI impact38:57 Future of generative AI in gaming and immersive content41:42 Coding agents, new LLMs, and local deployment45:40 AI model trends and data scientist career advice53:36 Cognitive testing, evaluation, and monitoring in AI58:50 Publishing details and closing remarksConnect with Micheal Linkedin - https://www.linkedin.com/in/micheal-lanham-189693123/Connect with DataTalks.Club: Join the community - https://datatalks.club/slack.htmlSubscribe to our Google calendar to have all our events in your calendar - https://calendar.google.com/calendar/...Check other upcoming events - https://lu.ma/dtc-eventsGitHub: https://github.com/DataTalksClubLinkedIn -   / datatalks-club   Twitter -   / datatalksclub   Website - https://datatalks.club/

    1 giờ
  2. 5 NGÀY TRƯỚC

    Berlin PyData 2025 Conference Interviews

    At PyData Berlin, community members and industry voices highlighted how AI and data tooling are evolving across knowledge graphs, MLOps, small-model fine-tuning, explainability, and developer advocacy. - Igor Kvachenok (Leuphana University / ProKube) combined knowledge graphs with LLMs for structured data extraction in the polymer industry, and noted how MLOps is shifting toward LLM-focused workflows. - Selim Nowicki (Distill Labs) introduced a platform that uses knowledge distillation to fine-tune smaller models efficiently, making model specialization faster and more accessible. - Gülsah Durmaz (Architect & Developer) shared her transition from architecture to coding, creating Python tools for design automation and volunteering with PyData through PyLadies. - Yashasvi Misra (Pure Storage) spoke on explainable AI, stressing accountability and compliance, and shared her perspective as both a data engineer and active Python community organizer. - Mehdi Ouazza (MotherDuck) reflected on developer advocacy through video, workshops, and branding, showing how creative communication boosts adoption of open-source tools like DuckDB. Igor Kvachenok Master’s student in Data Science at Leuphana University of Lüneburg, writing a thesis on LLM-enhanced data extraction for the polymer industry. Builds RDF knowledge graphs from semi-structured documents and works at ProKube on MLOps platforms powered by Kubeflow and Kubernetes. Connect: https://www.linkedin.com/in/igor-kvachenok/ Selim Nowicki Founder of Distill Labs, a startup making small-model fine-tuning simple and fast with knowledge distillation. Previously led data teams at Berlin startups like Delivery Hero, Trade Republic, and Tier Mobility. Sees parallels between today’s ML tooling and dbt’s impact on analytics. Connect: https://www.linkedin.com/in/selim-nowicki/ Gülsah Durmaz Architect turned developer, creating Python-based tools for architectural design automation with Rhino and Grasshopper. Active in PyLadies and a volunteer at PyData Berlin, she values the community for networking and learning, and aims to bring ML into architecture workflows. Connect: https://www.linkedin.com/in/gulsah-durmaz/ Yashasvi (Yashi) Misra Data Engineer at Pure Storage, community organizer with PyLadies India, PyCon India, and Women Techmakers. Advocates for inclusive spaces in tech and speaks on explainable AI, bridging her day-to-day in data engineering with her passion for ethical ML. Connect: https://www.linkedin.com/in/misrayashasvi/ Mehdi Ouazza Developer Advocate at MotherDuck, formerly a data engineer, now focused on building community and education around DuckDB. Runs popular YouTube channels ("mehdio DataTV" and "MotherDuck") and delivered a hands-on workshop at PyData Berlin. Blends technical clarity with creative storytelling. Connect: https://www.linkedin.com/in/mehd-io/

    49 phút
  3. 5 NGÀY TRƯỚC

    From Astronomy to Applied ML - Daniel Egbo

    In this episode, we talk with Daniel, an astrophysicist turned machine learning engineer and AI ambassador. Daniel shares his journey bridging astronomy and data science, how he leveraged live courses and public knowledge sharing to grow his skills, and his experiences working on cutting-edge radio astronomy projects and AI deployments. He also discusses practical advice for beginners in data and astronomy, and insights on career growth through community and continuous learning.TIMECODES00:00 Lunar eclipse story and Daniel’s astronomy career04:12 Electromagnetic spectrum and MEERKAT data explained10:39 Data analysis and positional cross-correlation challenges15:25 Physics behind radio star detection and observation limits16:35 Radio astronomy’s advantage and machine learning potential20:37 Radio astronomy progress and Daniel’s ML journey26:00 Python tools and experience with ZoomCamps31:26 Intel internship and exploring LLMs41:04 Sharing progress and course projects with orchestration tools44:49 Setting up Airflow 3.0 and building data pipelines47:39 AI startups, training resources, and NVIDIA courses50:20 Student access to education, NVIDIA experience, and beginner astronomy programs57:59 Skills, projects, and career advice for beginners59:19 Starting with data science or engineering1:00:07 Course sponsorship, data tools, and learning resourcesConnect with Daniel Linkedin -   / egbodaniel   Connect with DataTalks.Club: Join the community - https://datatalks.club/slack.htmlSubscribe to our Google calendar to have all our events in your calendar - https://calendar.google.com/calendar/...Check other upcoming events - https://lu.ma/dtc-eventsGitHub: https://github.com/DataTalksClubLinkedIn -   / datatalks-club   Twitter -   / datatalksclub   Website - https://datatalks.club/

    1 giờ 4 phút
  4. 12 THG 9

    Berlin Buzzwords 2025 Conference Interviews

    At Berlin Buzzwords, industry voices highlighted how search is evolving with AI and LLMs. - Kacper Łukawski (Qdrant) stressed hybrid search (semantic + keyword) as core for RAG systems and promoted efficient embedding models for smaller-scale use. - Manish Gill (ClickHouse) discussed auto-scaling OLAP databases on Kubernetes, combining infrastructure and database knowledge. - André Charton (Kleinanzeigen) reflected on scaling search for millions of classifieds, moving from Solr/Elasticsearch toward vector search, while returning to a hands-on technical role. - Filip Makraduli (Superlinked) introduced a vector-first framework that fuses multiple encoders into one representation for nuanced e-commerce and recommendation search. - Brian Goldin (Voyager Search) emphasized spatial context in retrieval, combining geospatial data with AI enrichment to add the “where” to search. - Atita Arora (Voyager Search) highlighted geospatial AI models, the renewed importance of retrieval in RAG, and the cautious but promising rise of AI agents. Together, their perspectives show a common thread: search is regaining center stage in AI—scaling, hybridization, multimodality, and domain-specific enrichment are shaping the next generation of retrieval systems. Kacper Łukawski Senior Developer Advocate at Qdrant, he educates users on vector and hybrid search. He highlighted Qdrant’s support for dense and sparse vectors, the role of search with LLMs, and his interest in cost-effective models like static embeddings for smaller companies and edge apps. Connect: https://www.linkedin.com/in/kacperlukawski/ Manish Gill Engineering Manager at ClickHouse, he spoke about running ClickHouse on Kubernetes, tackling auto-scaling and stateful sets. His team focuses on making ClickHouse scale automatically in the cloud. He credited its speed to careful engineering and reflected on the shift from IC to manager. Connect: https://www.linkedin.com/in/manishgill/ André Charton Head of Search at Kleinanzeigen, he discussed shaping the company’s search tech—moving from Solr to Elasticsearch and now vector search with Vespa. Kleinanzeigen handles 60M items, 1M new listings daily, and 50k requests/sec. André explained his career shift back to hands-on engineering. Connect: https://www.linkedin.com/in/andrecharton/ Filip Makraduli Founding ML DevRel engineer at Superlinked, an open-source framework for AI search and recommendations. Its vector-first approach fuses multiple encoders (text, images, structured fields) into composite vectors for single-shot retrieval. His Berlin Buzzwords demo showed e-commerce search with natural-language queries and filters. Connect: https://www.linkedin.com/in/filipmakraduli/ Brian Goldin Founder and CEO of Voyager Search, which began with geospatial search and expanded into documents and metadata enrichment. Voyager indexes spatial data and enriches pipelines with NLP, OCR, and AI models to detect entities like oil spills or windmills. He stressed adding spatial context (“the where”) as critical for search and highlighted Voyager’s 12 years of enterprise experience. Connect: https://www.linkedin.com/in/brian-goldin-04170a1/ Atita Arora Director of AI at Voyager Search, with nearly 20 years in retrieval systems, now focused on geospatial AI for Earth observation data. At Berlin Buzzwords she hosted sessions, attended talks on Lucene, GPUs, and Solr, and emphasized retrieval quality in RAG systems. She is cautiously optimistic about AI agents and values the event as both learning hub and professional reunion. Connect: https://www.linkedin.com/in/atitaarora/

    1 giờ 8 phút
  5. 22 THG 8

    From Medicine to Machine Learning: How Public Learning Turned into a Career - Pastor Soto

    In this episode, We talked with Pastor, a medical doctor who built a career in machine learning while studying medicine. Pastor shares how he balanced both fields, leveraged live courses and public sharing to grow his skills, and found opportunities through freelancing and mentoring.TIMECODES00:00 Pastor’s background and early programming journey06:05 Learning new tools and skills on the job while studying medicine11:44 Balancing medical studies with data science work and motivation13:48 Applying medical knowledge to data science and vice versa18:44 Starting freelance work on Upwork and overcoming language challenges24:03 Joining the machine learning engineering course and benefits of live cohorts27:41 Engaging with the course community and sharing progress publicly35:16 Using LinkedIn and social media for career growth and interview opportunities41:03 Building reputation, structuring learning, and leveraging course projects50:53 Volunteering and mentoring with DeepLearning.AI and Stanford Coding Place57:00 Managing time and staying productive while studying medicine and machine learningConnect with Pastor Twitter - https://x.com/PastorSotoB1Linkedin -   / pastorsoto  Github - https://github.com/sotoblancoWebsite - https://substack.com/@pastorsotoConnect with DataTalks.Club: Join the community - https://datatalks.club/slack.htmlSubscribe to our Google calendar to have all our events in your calendar - https://calendar.google.com/calendar/...Check other upcoming events - https://lu.ma/dtc-eventsGitHub: https://github.com/DataTalksClubLinkedIn -   / datatalks-club   Twitter -   / datatalksclub   Website - https://datatalks.club/

    1 giờ
  6. 15 THG 8

    How to Rebuild Data Trust? Mindful Data Strategy and Maintenance vs Innovation - Lior Barak

    Struggling with data trust issues, dashboard drama, or constant pipeline firefighting? In this deep‑dive interview, Lior Barak shows you how to shift from a reactive “fix‑it” culture to a mindful, impact‑driven practice rooted in Zen/Wabi‑Sabi principles. You’ll learn: Why 97 % of CEOs say they use data, but only 24 % call themselves data‑driven The traffic‑light dashboard pattern (green / yellow / red) that instantly tells execs whether numbers are safe to use A practical rule for balancing maintenance, rollout, and innovation—and avoiding team burnout How to quantify ROI on data products, kill failing legacy systems, and handle ad‑hoc exec requests without derailing roadmaps Turning “imperfect” data into business value with mindful communication, root‑cause logs, and automated incident review loops 🕒 TIMECODES 00:00 Community and mindful data strategy 04:06 Career journey and product management insights 08:03 Wabi-sabi data and the trust crisis 11:47 AI, data imperfection, and trust challenges 20:05 Trust crisis examples and root cause analysis 25:06 Regaining trust through mindful data management 30:47 Traffic light system and effective communication 37:41 Communication gaps and team workload balance 39:58 Maintenance stress and embracing Zen mindset 49:29 Accepting imperfection and measuring impact 56:19 Legacy systems and managing executive requests 01:00:23 Role guidance and closing reflections 🔗 Connect with Lior LinkedIn - https://www.linkedin.com/in/liorbarak Website - https://cookingdata.substack.com/ Cooking Data newsletter: https://cookingdata.substack.com/ Product product lifecycle manager: https://app--data-product-lifecycle-manager-c81b10bb.base44.app/ 🔗 Connect with DataTalks.Club Join the community - https://datatalks.club/slack.html Subscribe to our Google calendar to have all our events in your calendar - https://calendar.google.com/calendar/u/0/r?cid=ZjhxaWRqbnEwamhzY3A4ODA5azFlZ2hzNjBAZ3JvdXAuY2FsZW5kYXIuZ29vZ2xlLmNvbQ Check other upcoming events - https://lu.ma/dtc-events GitHub: https://github.com/DataTalksClub LinkedIn - https://www.linkedin.com/company/datatalks-club/ Twitter - https://x.com/DataTalksClub Website - https://datatalks.club/ 🔗 Connect with Alexey Twitter - https://x.com/Al_Grigor Linkedin - https://www.linkedin.com/in/agrigorev/

    1 giờ 2 phút
  7. 1 THG 8

    From Simulations to Freelance Data Engineering: Orell's Journey Out of Academia and Into Consulting - Orell Garten

    In this episode, we talk with Orell about his journey from electrical engineering to freelancing in data engineering. Exploring lessons from startup life, working with messy industrial data, the realities of freelancing, and how to stay up to date with new tools. Topics covered: Why Orel left a PhD and a simulation‑focused start‑up after Covid hitWhat he learned trying (and failing) to commercialise medical‑imaging simulationsThe first freelance project and the long, quiet months that followedHow he now finds clients, keeps projects small and delivers value quicklyTypical work he does for industrial companies: parsing messy machine logs, building simple pipelines, adding structure laterFavorite everyday tools (Python, DuckDB, a bit of C++) and the habit of blocking time for learningAdvice for anyone thinking about freelancing: cash runway, networking, and focusing on problems rather than “perfect” tech choices A practical conversation for listeners who are curious about moving from research or permanent roles into freelance data engineering. 🕒 TIMECODES 0:00 Orel’s career and move to freelancing 9:04 Startup experience and data engineering lessons 16:05 Academia vs. startups and starting freelancing 25:33 Early freelancing challenges and networking 34:22 Freelance data engineering and messy industrial data 43:27 Staying practical, learning tools, and growth 50:33 Freelancing challenges and client acquisition 58:37 Tools, problem-solving, and manual work 🔗 CONNECT WITH ORELL Twitter - https://bsky.app/profile/orgarten.bsk... LinkedIn - / ogarten Github - https://github.com/orgarten Website - https://orellgarten.com 🔗 CONNECT WITH DataTalksClub Join the community - https://datatalks.club/slack.html Subscribe to our Google calendar to have all our events in your calendar - https://calendar.google.com/calendar/... Check other upcoming events - https://lu.ma/dtc-events GitHub: https://github.com/DataTalksClub LinkedIn - / datatalks-club Twitter - / datatalksclub Website - https://datatalks.club/ 🔗 CONNECT WITH ALEXEY Connect with Alexey Twitter - / al_grigor Linkedin - / agrigorev

    58 phút
  8. 25 THG 7

    Can You Quit Your Job and Still Succeed as a Data Freelancer?

    Thinking about swapping your 9‑to‑5 for client work, but worried that a long German–style notice period will kill your chances?  In this live interview, seven‑year data‑freelance veteran Dimitri walks through his experience of taking his freelance career to the next level. About the Speaker: Dimitri Visnadi is an independent data consultant with a focus on data strategy. He has been consulting companies leading the marketing data space such as Unilever, Ferrero, Heineken, and Red Bull. He has lived and worked in 6 countries across Europe in both corporate and startup organizations. He was part of data departments at Hewlett-Packard (HP) and a Google partnered consulting firm where he was working on data products and strategy. Having received a Masters in Business Analytics with Computer Science from University College London and a Bachelor in Business Administration from John Cabot University, Dimitri still has close ties to academia and holds a mentor position in entrepreneurship at both institutions. 🕒 TIMECODES00:00 Dimitri’s journey from corporate to freelance data specialist05:41 Job tenure trends, tech career shifts, and freelance types10:50 Freelancing challenges, success, and finding clients17:33 Freelance market trends and Dimitri’s job board23:51 Starting points, top freelance skills, and market insights32:48 Building a lifestyle business: scaling and work-life balance45:30 Data Freelancer course and marketing for freelancers48:33 Subscription services and managing client relationships56:47 Pricing models and transitioning advice1:01:02 Notice periods, networking, and risks in freelancing transition 🔗 CONNECT WITH DataTalksClub Join the community - https://datatalks.club/slack.html Subscribe to our Google calendar to have all our events in your calendar - https://calendar.google.com/calendar/... Check other upcoming events - https://lu.ma/dtc-events LinkedIn - / datatalks-club Twitter - / datatalksclub Website - https://datatalks.club/ 🔗 CONNECT WITH DIMITRI Linkedin - https://www.linkedin.com/in/visnadi/

    58 phút

Xếp Hạng & Nhận Xét

5
/5
7 Xếp hạng

Giới Thiệu

DataTalks.Club - the place to talk about data!

Có Thể Bạn Cũng Thích