DataTalks.Club

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

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

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

We talked about: Jack’s background Transitioning from IC to management Lesson not taught in traditional school The importance of people’s perception, trust, and respect How soft skills are relevant to machine learning How to put on a salesman hat in machine learning management The importance of visuals and building a POC as fast as possible 1st Rule of Machine Learning – don’t be afraid to start without machine learning The importance of understanding the reality that data represents The importance of putting yourself in the shoes of customers The importance of software engineering skills in machine learning Where to find Jack’s content Jack’s next venture Links: Jack's LinkedIn profile: https://www.linkedin.com/in/jackblandin/ Free ML Engineering course: http://mlzoomcamp.com Join DataTalks.Club: https://datatalks.club/slack.html Our events: https://datatalks.club/events.html

Links: Mini sound bath: https://www.youtube.com/watch?v=g-lDrcSqcrQ Free ML Engineering course: http://mlzoomcamp.com Join DataTalks.Club: https://datatalks.club/slack.html Our events: https://datatalks.club/events.html