You can cover a lot of ground while listening to podcasts. And diversity in podcasts is huge.

Comments URL: https://news.ycombinator.com/item?id=48975692

Points: 1

# Comments: 0

Biggest problem OpenAI has is not having an immense data backbone like Meta/Google/MSFT has. I think this is step in that direction -- create a data moat which in turn will help them make better models.

I come from a tech background but want to explore the energy industry (especially renewables) with the goal of eventually starting something of my own.

From my initial exposure, I’ve realized there are many opportunities to make life easier for companies in this sector. My usual approach has been to study extensively first and then reach out to people to fill the gaps. However, based on advice from 2 founders I recently met, I’d like to flip this approach: starting with conversations with experienced leaders and professionals to understand the practical realities of the industry.

My request: if you are currently working, have worked, know someone in this field, or simply have deep knowledge of it -- and are willing to share 30-60 minutes of your time -- I’d be truly grateful.

Best regards, Shivam

Comments URL: https://news.ycombinator.com/item?id=45366613

Points: 5

# Comments: 0

Comments URL: https://news.ycombinator.com/item?id=42687148

Points: 57

# Comments: 3

Now I have started taking advantage of this using Anki. Whenever I read something having a particularly interesting or thought-provoking idea, I find a way to create flashcard(s) out of it. Now I am able to recall these things more often and many times they have guided me in my life or helping out friends.

Remote: Yes

Willing to relocate: Yes (UK, EU, US)

Technologies: Python, SQL, PySpark, Git, Linux, MS Excel, PyTorch

Résumé/CV: https://www.linkedin.com/in/tminima

Email: shivam_r@outlook.com

Blog: http://shivamrana.me

Domain: Recommendation Systems, NLP (Translation, Language Modeling), Classification Algorithms, Regression Algorithms, Deep Learning (Seq2Seq, Transformer, RNN, LSTM, GRU, CNN), Data Scraping, Visualization (matplotlib, ggplot2).

I am Senior Data Scientist with ~8 years of experience in Data Science. For the last three years, I have been working on Recommendation Engines for a B2C company. I have deployed 30+ models in production, receiving more than 400k QPS traffic. I have seen e2e journey of multiple data science projects: business problem -> formulation -> offline training/eval -> deployment -> A/B testing -> Scaling up -> Monitoring. In my new role, I am looking to apply my experience to design e2e ML systems.

Along with embed link, I was wondering if there is a way to download the HTML of the rendered timeline directly. I use static pages for my blog and would love a way to add the rendered output directly.

I write about random experiments I do in my life (data science, personal analytics, reviews, travel, etc). Been travelling a lot this year, but haven't been able to write about it much. Hoping to change that in the next few weeks.

Comments URL: https://news.ycombinator.com/item?id=36268329

Points: 2

# Comments: 0

Haven't been able to spend time on this. I want to improve the following 2 things first:

- Travel page: have those hover on the map and see where all I have travelled.

- Landing page: I want to change the landing page to a portfolio page where I have a stackoverflow type developer timeline thing.

Sadly, I don't have much experience in web technologies, so not sure how to even start with these things.

Comments URL: https://news.ycombinator.com/item?id=26190924

Points: 2

# Comments: 0

Comments URL: https://news.ycombinator.com/item?id=26173557

Points: 3

# Comments: 0

I recently created an open source website[1] having a collection of podcasts about Machine Learning, Data Science, and ML Engineering. The podcast details are updated daily using GitHub actions. The source is available at the GitHub Repo[2]. Adding a new podcast is easy: just add a simple text file with YAML front matter. I want the website to become a go-to place where people find the next Data Science podcast they want to listen to. I have plans to make podcast pages more informative. My objectives of sharing the website are three-fold:

1. Share this resource with people here who might be interested in podcasts.

2. Feedback and suggestions about what more information can be added to make the discovery and selection process for users easier.

3. If people have any additions to the current list, I am happy to add them.

Hope this helps the community. People on r/machinelearning[3] liked it.

---

[1]: http://dspods.netlify.app/

[2]: https://github.com/TrigonaMinima/dspods

[3]: https://www.reddit.com/r/MachineLearning/comments/liz35x/d_p...