We talked about:

Tereza’s background Switching from an Individual Contributor to Lead Python Pizza and the pizza management metaphor Learning to figure things out on your own and how to receive feedback Tereza as a leadership coach Podcasts Tereza’s coaching framework (selling yourself vs bragging) The importance of retrospectives The importance of communication and active listening Convincing people you don’t have power over Building relationships and empathy Inclusive leadership

Links:

LinkedIn: https://www.linkedin.com/in/tereza-iofciu/ Twitter: https://twitter.com/terezaif Github: https://github.com/terezaif Website: https:// terezaiofciu.com

Free Data Engineering course: https://github.com/DataTalksClub/data-engineering-zoomcamp

Join DataTalks.Club: https://datatalks.club/slack.html Our events: https://datatalks.club/events.html

Links:

VectorHub: https://superlinked.com/vectorhub/?utm_source=community&utm_medium=podcast&utm_campaign=datatalks Daniel's LinkedIn: https://www.linkedin.com/in/svonava/

Free Data Engineering course: https://github.com/DataTalksClub/data-engineering-zoomcamp

Join DataTalks.Club: https://datatalks.club/slack.html Our events: https://datatalks.club/events.html

​This podcast is sponsored by VectorHub, a free open-source learning community for all things vector embeddings and information retrieval systems.

Today’s episode is a re-release from Season 1! Join hosts Shane Safir and Alcine Mumby as they dig deep with Dr. Christopher Emdin around how to be a good ancestor, biomimicry as a guide to school transformation, burning the pedagogical sage, and so much more. This episode will change you! A must-listen for all new administrators and teachers finding their way in complex times.

For Further Learning:

Order Chris’s book Rathedemic at http://www.beacon.org/Ratchetdemic-P1703.aspx Read Chris’s foreword in Street Data to make connections to the pod conversation Order adrienne marie brown’s Emergent Strategy at https://www.akpress.org/emergentstrategy.html

We talked about:

Reem’s background Context-aware sensing and transfer learning Shifting focus from PhD to industry Reem’s experience with startups and dealing with prejudices towards PhDs AI interviewing solution How candidates react to getting interviewed by an AI avatar End-to-end overview of a machine learning project The pitfalls of using LLMs in your process Mitigating biases Addressing specific requirements for specific roles Reem’s resource recommendations

Links:

LinkedIn: https://www.linkedin.com/in/reemmahmoud/recent-activity/all/ Website: https://topmate.io/reem_mahmoud

Free Data Engineering course: https://github.com/DataTalksClub/data-engineering-zoomcamp Join DataTalks.Club: https://datatalks.club/slack.html Our events: https://datatalks.club/events.html

We talked about:

Sara’s background On being a Google PhD fellow Sara’s volunteer work Finding AI volunteer work Sara’s Fruit Punch challenge How to take part in AI challenges AI Wonder Girls Hackathons Things people often miss in AI projects and hackathons Getting creative Fostering your social media Tips on applying for volunteer projects Why it’s worth doing volunteer projects Opportunities for data engineers and students Sara’s newsletter suggestions

Links:

Dev and AI hackathons: https://devpost.com/ Healthcare-focused challenges: https://grand-challenge.org/challenges/ Volunteering in projects (AI4Good): https://www.fruitpunch.ai/ Volunteering in projects (AI4Good) 2: https://www.omdena.com/ Twitter: https://twitter.com/el_ateifSara Instagram: https://www.instagram.com/saraelateif/ LinkedIn: https://www.linkedin.com/in/sara-el-ateif/ Youtube: www.youtube.com/@elateifsara

Free Data Engineering course: https://github.com/DataTalksClub/data-engineering-zoomcamp Join DataTalks.Club: https://datatalks.club/slack.html Our events: https://datatalks.club/events.html

This session will be an introduction to using React as your frontend library. Basic knowledge of HTML, CSS, and JavaScript is required for you to understand what is going on.

If programming is magic, then web scraping is surely a form of wizardry. By writing a simple automated program, you can query web servers, request data, and parse it to extract the information you need. This thoroughly updated third edition not only introduces you to web scraping but also serves as a comprehensive guide to scraping almost every type of data from the modern web. Part I focuses on web scraping mechanics: using Python to request information from a web server, performing basic handling of the server's response, and interacting with sites in an automated fashion. Part II explores a variety of more specific tools and applications to fit any web scraping scenario you're likely to encounter. Parse complicated HTML pages Develop crawlers with the Scrapy framework Learn methods to store the data you scrape Read and extract data from documents Clean and normalize badly formatted data Read and write natural languages Crawl through forms and logins Scrape JavaScript and crawl through APIs Use and write image-to-text software Avoid scraping traps and bot blockers Use scrapers to test your website

We talked about:

Sarah’s background How Sarah became a coach and found her niche Sarah’s clients How Sarah helps her clients find the perfect job Finding a specialization Informational interviews Building a connection for mutual benefit The networking strategy Listing your projects in the CV The importance of doing research yourself and establishing your interests How to land a part-time job when the company wants full-time Age is not a factor Applying for jobs after finishing a course and the importance of sharing your learnings Sarah resource recommendations

Links:

LinkedIn: https://www.linkedin.com/in/sarahmestiri/ Website: https://thrivingcareermoms.com/ Personal Website: https://www.sarahmestiri.com/ Youtube channel: https://www.youtube.com/@thrivingcareermoms444

Free Data Engineering course: https://github.com/DataTalksClub/data-engineering-zoomcamp Join DataTalks.Club: https://datatalks.club/slack.html Our events: https://datatalks.club/events.html

We talked about:

Nemanja’s background

When Nemanja first work as a data person Typical problems that ML Ops folks solve in the financial sector What Nemanja currently does as an ML Engineer The obstacle of implementing new things in financial sector companies Going through the hurdles of DevOps Working with an on-premises cluster “ML Ops on a Shoestring” (You don’t need fancy stuff to start w/ ML Ops) Tactical solutions Platform work and code work Programming and soft skills needed to be an ML Engineer The challenges of transitioning from and electrical engineering and sales to ML Ops The ML Ops tech stack for beginners Working on projects to determine which skills you need

Links:

LinkedIn: https://www.linkedin.com/in/radojkovic/

Free Data Engineering course: https://github.com/DataTalksClub/data-engineering-zoomcamp

Join DataTalks.Club: https://datatalks.club/slack.html Our events: https://datatalks.club/events.html

From a cluster of interconnected HTML pages to online service platforms, websites are constantly changing in form and function. These transformations have led, on the one hand, to human and social sciences renewing or inventing analytical methodologies; and on the other hand, to a reconsideration of the practices of non-specialists and digital professionals. The Web factory is equally included on the agenda of communication training, according to an alternative approach that is complementary to the one that has been implemented for computer scientists. From these two perspectives and drawing upon several case studies, Analyzing Websites presents epistemological and methodological contributions from researchers in Information and Communication Sciences exploring websites as sociotechnical, semi-discursive and communicational devices. This study covers website design as well as their integration into the digital strategies of organizations in the public, associative and private sectors.

We talked about:

Ivan’s background How Ivan became interested in investing Getting financial data to run simulations Open, High, Low, Close, Volume Risk management strategy Testing your trading strategies Sticking to your strategy Important metrics and remembering about trading fees Important features Deployment How DataTalks.Club courses helped Ivan Ivan’s site and course sign-up

Links:

Exploring Finance APIs: https://pythoninvest.com/long-read/exploring-finance-apis Python Invest Blog Articles: https://pythoninvest.com/blog

Free ML Engineering course: http://mlzoomcamp.com Join DataTalks.Club: https://datatalks.club/slack.html Our events: https://datatalks.club/events.html

We talked about:

Rob’s background Going from software engineering to Bayesian modeling Frequentist vs Bayesian modeling approach About integrals Probabilistic programming and samplers MCMC and Hakaru Language vs library Encoding dependencies and relationships into a model Stan, HMC (Hamiltonian Monte Carlo) , and NUTS Sources for learning about Bayesian modeling Reaching out to Rob

Links:

Book 1: https://bayesiancomputationbook.com/welcome.html Book/Course: https://xcelab.net/rm/statistical-rethinking/

Free ML Engineering course: http://mlzoomcamp.com Join DataTalks.Club: https://datatalks.club/slack.html Our events: https://datatalks.club/events.html

We talked about:

Atita’s background How NLP relates to search Atita’s experience with Lucidworks and OpenSource Connections Atita’s experience with Qdrant and vector databases Utilizing vector search Major changes to search Atita has noticed throughout her career RAG (Retrieval-Augmented Generation) Building a chatbot out of transcripts with LLMs Ingesting the data and evaluating the results Keeping humans in the loop Application of vector databases for machine learning Collaborative filtering Atita’s resource recommendations

Links:

LinkedIn: https://www.linkedin.com/in/atitaarora/
Twitter: https://x.com/atitaarora Github: https://github.com/atarora Human-in-the-Loop Machine Learning: https://www.manning.com/books/human-in-the-loop-machine-learning Relevant Search: https://www.manning.com/books/relevant-search Let's learn about Vectors: https://hub.superlinked.com/ Langchain: https://python.langchain.com/docs/get_started/introduction Qdrant blog: https://blog.qdrant.tech/ OpenSource Connections Blog: https://opensourceconnections.com/blog/

Free ML Engineering course: http://mlzoomcamp.com Join DataTalks.Club: https://datatalks.club/slack.html Our events: https://datatalks.club/events.html

We talked about:

Adrian’s background The benefits of freelancing Having an agency vs freelancing What let Adrian switch over from freelancing The conception of DLT (Growth Full Stack) The investment required to start a company Growth through the provision of services Growth through teaching (product-market fit) Moving on to creating docs Adrian’s current role Strategic partnerships and community growth through DocDB Plans for the future of DLT DLT vs Airbyte vs Fivetran Adrian’s resource recommendations

Links:

Adrian's LinkedIn: https://www.linkedin.com/in/data-team/ Twitter: https://twitter.com/dlt_library Github: https://github.com/dlt-hub/dlt Website: https://dlthub.com/docs/intro

Free ML Engineering course: http://mlzoomcamp.com Join DataTalks.Club: https://datatalks.club/slack.html Our events: https://datatalks.club/events.html

We talked about:

Dimitri’s background The first steps of transitioning into freelance Working with recruiters (contracting) Deciding on what to charge for your services Establishing your network Self-marketing Contracting vs freelancing Which channel is better for those starting out? Cutting out the middleman Where to look for clients and how to vet them The different way of getting into freelancing Going back to a full-time job after freelancing Common mistakes freelancers make Dimitri’s resource suggestions Reaching out to Dimitri

Links:

LinkedIn profile: http://www.linkedin.com/in/visnadi The DataFreelancer website: https://thedatafreelancer.com/

Free ML Engineering course: http://mlzoomcamp.com Join DataTalks.Club: https://datatalks.club/slack.html Our events: https://datatalks.club/events.html

We talked about:

Maria’s background Deciding to go into telecare (healthcare) Current difficulties in healthcare Getting into the healthcare industry as a lifestyle brand The importance of a plan B and being flexible What is SQIN and the importance of communication Going from lipstick to skin health analysis The importance of community and broadening your audience The importance of feedback and communicating benefits The current state and growth of SQIN Convincing investors and the importance of proving profitability Maria’s role at SQIN Balancing a newborn child and a new company

Links:

Free ML Engineering course: http://mlzoomcamp.com Join DataTalks.Club: https://datatalks.club/slack.html Our events: https://datatalks.club/events.html

Bring your data into the era of AI with Microsoft Fabric, a powerful all in one AI powered analytics solution for enterprises that covers everything from data movement to data science, real time analytics and business intelligence. Learn how Azure Databricks and Microsoft Fabric seamlessly work together to offer customers a modern, price performant analytics solution that helps teams turn data into a competitive advantage.

To learn more, please check out these resources: * https://aka.ms/Ignite23CollectionsBRK221H * https://info.microsoft.com/ww-landing-contact-me-for-events-m365-in-person-events.html?LCID=en-us&ls=407628-contactme-formfill * https://aka.ms/azure-ignite2023-dataaiblog

𝗦𝗽𝗲𝗮𝗸𝗲𝗿𝘀: * Justyna Lucznik * Kristen Christensen * Patrick Baumgartner * Eric McChesney * Hannah Chen * Wangui wmckelvey * Arthi Ramasubramanian Iyer * Chris Finlan * Christian Wade * Ed Donahue * Kasper de Jonge * Mohammad Ali * Ravs Kaur * Steve Howard * Jessica Hawk * Amir Netz * Arun Ulagaratchagan

𝗦𝗲𝘀𝘀𝗶𝗼𝗻 𝗜𝗻𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻: This video is one of many sessions delivered for the Microsoft Ignite 2023 event. View sessions on-demand and learn more about Microsoft Ignite at https://ignite.microsoft.com

BRK221H | English (US) | Data

MSIgnite

We talked about:

Christoph’s background Kaggle and other competitions How Christoph became interested in interpretable machine learning Interpretability vs Accuracy Christoph’s current competition engagement How Christoph chooses topics for books Why Christoph started the writing journey with a book Self-publishing vs via a publisher Christoph’s other books What is conformal prediction? Christoph’s book on SHAP Explainable AI vs Interpretable AI Working alone vs with other people Christoph’s other engagements and how to stay hands-on Keeping a logbook Does one have to be an expert on the topic to write a book about it? Writing in the open and other feedback gathering methods Advice for those who want to be technical writers Self-publishing tools Finding Christoph online

Links:

LinkedIn: https://www.linkedin.com/in/christoph-molnar/ Website: https://christophmolnar.com/

Free ML Engineering course: http://mlzoomcamp.com Join DataTalks.Club: https://datatalks.club/slack.html Our events: https://datatalks.club/events.html

Prompt engineering and LLMOps are pivotal in maximizing the capabilities of Language Models (LLMs) for specific business needs. This session offers a comprehensive guide to Azure AI's latest features that simplify the AI application development cycle. We'll walk you through the entire process—from prototyping and experimenting to evaluating and deploying your AI-powered apps. Learn how to streamline your AI workflows and harness the full potential of Generative AI with Azure AI Studio.

To learn more, please check out these resources: * https://aka.ms/Ignite23CollectionsBRK203H * https://info.microsoft.com/ww-landing-contact-me-for-events-m365-in-person-events.html?LCID=en-us&ls=407628-contactme-formfill * https://aka.ms/azure-ignite2023-dataaiblog

𝗦𝗽𝗲𝗮𝗸𝗲𝗿𝘀: * Cassie Breviu * Daniel Schneider * Bozhong Lin * Jessica Cioffi * Ed Donahue * Meng Tang * Takuto Higuchi * Greg Buehrer * Jithendra Veeramachaneni

𝗦𝗲𝘀𝘀𝗶𝗼𝗻 𝗜𝗻𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻: This video is one of many sessions delivered for the Microsoft Ignite 2023 event. View sessions on-demand and learn more about Microsoft Ignite at https://ignite.microsoft.com

BRK203 | English (US) | AI & Apps

MSIgnite

From Chat GPT to the NBA to Mercedes-Benz, Azure Cosmos DB is enabling intelligent apps that change the way we live and work. Join us to learn from KPMG about how they built a generative AI-based assistant, and Bond Brand Loyalty on how they scale data to meet global customer demand, with Azure Cosmos DB. We'll explore capabilities like vector search and how to implement RAG pattern, along with improved elasticity, and greater scale.

To learn more, please check out these resources: * https://aka.ms/Ignite23CollectionsBRK226H * https://info.microsoft.com/ww-landing-contact-me-for-events-m365-in-person-events.html?LCID=en-us&ls=407628-contactme-formfill * https://aka.ms/azure-ignite2023-dataaiblog

𝗦𝗽𝗲𝗮𝗸𝗲𝗿𝘀: * James Codella * Kirill Gavrylyuk * Maria Pallante * Mark Brown * Robert Finlayson * Anitha Adusumilli * Estefani Arroyo * Andrew Liu * Marko Hotti * Rodrigo Souza * Jason Fogaty

𝗦𝗲𝘀𝘀𝗶𝗼𝗻 𝗜𝗻𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻: This video is one of many sessions delivered for the Microsoft Ignite 2023 event. View sessions on-demand and learn more about Microsoft Ignite at https://ignite.microsoft.com

BRK226HG | English (US) | Data

MSIgnite