I work on a trading desk and right now they've mainly been asking me to do more data engineering and ad hoc analysis work. There was a past modeling project with some regressions written in R. I'm basically the only data scientist/technologist on the trading desk, but I have a lot of flexibility in terms of what I can work, but I would just need to justify in terms of providing business impact. How do you justify investing time into machine learning/modeling projects to your business stakeholders? submitted by /u/Ambitious-Wolf-2439 [link] [comments]

I'm needing some extra money and I could certainly use a second income right now. However, I know nothing about freelancing besides that some platforms help with that like fiverr and upwork. Should I simply subscribe in one of these platforms? Should I try to start on linkedin? I'd like to work with the delivery of data analysis projects with AI models or dashboard creation with Power BI (these are my main skills). ​ Any tips? submitted by /u/Traditional-Reach818 [link] [comments]

How many features are typically used in a model? In my work, for example, using XGBoost, my boss selects the top 40 most important features based on a certain score, and we use between 30 and 20 of those features. The minimum number of features we have used is 16. While using 20 features doesn't seem to cause overfitting, it still feels like a lot. And also how can i deal with a client that ask to include 30 variables? submitted by /u/bebu17 [link] [comments]

My company is offering to pay my way to a conference or workshop or similar to advance my skills. Where should I go? We're in the healthcare space. I'm sort of a jack-of-all-trades so I'm open to a lot of stuff. Perhaps optimization would be a good area, or generative neural networks. What are the biggest & best overall DS conferences? Healthcare specifically? Is there a good GNN conference/workshop? submitted by /u/GlitteringBusiness22 [link] [comments]

Hey guys, Recently got hired as a data professional. Today marks 1 week. Am getting up to the business pretty fast. I work in a healthcare organization. So I don't know much of the stuff like why are they storing this the way they do and whatnot. Today I had a meeting with my supervisor and my teammate/mentor (kind of) to discuss various medical forms. My teammate/current mentor is not a data pro and they were the one who handled the basic data tasks during covid. And in today's meeting shit hit the fan. I asked questions today regarding the various fields of different forms and tried to find out why they use certain fields and suggested ways that might be better for storing data. Basically I asked questions. And for some reason, my teammate/mentor cut me down. Like they gave off a vibe as if I'm asking stupid questions. Most of the answers were 'but that's not a metric we are tracking right now'. As I was in the middle of it, the one thing that got repeated in my head was 'am I dumb for asking questions like this?' Because... I felt dumb. Like my supervisor asked me if we can do a certain thing, to which I answered sure but I'd have to know if data extraction from your system (CRM) fetches data that is locked as well as unlocked or just locked (internal terminology to decide if the form is completed). My teammate just ignored the question and went on about how it could be done an easier way. Like wtf. Like I'd at least like to know for future references if not for the current usecase. Just answer the question! Maybe this is office politics, because I'm basically taking over the tasks that my teammate/mentor used to do. Maybe its because I'm not understandsing something. Idk. My mind is pretty fucked rn. Tldr I asked some questions, got unsatisfactory answers or got completely ignored by my teammate/mentor. submitted by /u/thanderrine [link] [comments]

submitted by /u/I_like_warm_blankets [link] [comments]

Regardless of its change in course from where it started, when I compare the leadership at openAI to other big tech businesses, I think we lucked out with openai. I see lots of hate for sam and openAI online. TBH it's a matter of time before someone goes and does something like a network of semi-autonomous auto-GPT's planning and executing all sorts of chaos/attacks so I think getting ahead of things like this and talking about some type of regulation is perfectly warranted. Also I don't know if you listened to the court hearing but he specifically said that the regulation needs to be focused on Google, Microsoft, and openAI and other large competitors rather than open source (ofc open-source will be affected). Although I don't want heavy regulation, it seems like a lot of people want almost no regulation which is very odd to me. (Also bringing competition to google is a huge bonus) submitted by /u/Initial-Doughnut-765 [link] [comments]

Hello, I am currently an MLOps engineer in my company. I help data scientists create tools and assist with deployment problems. Perhaps I have come to hate learning DevOps stuff, such as Terraform, data permissions, security, etc. Initially, my first idea was to work as a data scientist. However, I gave up on that idea since I have ADHD (although I didn't know it at the time). However, five months ago, I started treatment for my ADHD problem, and I began to gain confidence. Today, I spoke with my boss, and he said I can transition to becoming a data scientist. However, it will take some time because I am not too good with business-related matters, and I need to improve my communication skills. Due to my ADHD, I have always struggled with impulsive problems in my speech. I have also been thinking about trying to apply for jobs. However, I am not currently confident enough to do so. submitted by /u/Muted_Standard175 [link] [comments]

I'm a data Scientist with 6+ years of experience. Doing this shift is something that has crossed my mind a few times in the last 2 years but now it seems the right time for me to start a study plan to accomplish this. I like both the stats and the programming part of Data Scientist but I'm getting quite frustrated at the lack of remote job opportunities for Data Scientist. It seems many company think that DS should be as close as possible to the business people, hence enforcing RTO. With devs and data engineers it seems much there are many more WFH from home, even for companies outside of my country (Brazil). Thoughts on doing this transition? What's a study plan like to becoming a data or software engineer given my technical background? submitted by /u/CadeOCarimbo [link] [comments]

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Hi, I am a new immigrant to Canada who is trying to find Data Scientist opportunities in this brutal market. I have around 4+ years of relevant experience and a Master's degree in engineering from my home country under my belt. I am working at a small company currently. However, I am finding it hard to move to a better/bigger opportunity. I was able to get to the final rounds of interviews at the handful of companies and at least 3 of the opportunities I lost to folks having Master's from Canadian University which makes me wonder if I should go back to university. At the same time I am not sure whether I am ready for such big commitment (time and finance wise) at this point in my life. I see these online Master's programs. Can someone tell me how valuable are they in the job market? submitted by /u/ExcuseNo6720 [link] [comments]

Hi all I'm a mathematician/process/statistical modeller working in agricultural/environmental science. Our company has invested in Snowflake for data storage and R for data analysis. However I am finding that the volumes of data are becoming a bit more than can be comfortably handled in R on a single PC (we're in Windows 10). I am looking for options for data visualisation, extraction, cleaning, statistical modelling that don't require downloading the data and/or having it in memory. I don't really understand the IT side of data science very well, but two options look like Spark(lyr) and Snowpark. Any suggestions or advice or experience you can share? Thanks! submitted by /u/si_wo [link] [comments]

We wanted to share our recent review paper “Machine learning for ancient languages: a survey” published in Computational Linguistics (MIT Press). Our work surveyed over 240 research papers using machine learning for the study of ancient texts written in any language, script and medium. This review is intended to promote and support the continued collaborative impetus between the Humanities and Machine Learning, and is a part of our effort on AI for the Humanities. https://direct.mit.edu/coli/article/doi/10.1162/coli_a_00481/116160/Machine-Learning-for-Ancient-Languages-A-Survey We also created a GitHub repository to host the taxonomy of the reviewed literature and maintain an up-to-date catalogue of active interdisciplinary research on this theme (pull requests encouraged!) https://github.com/ancientml/ml-for-ancient-languages submitted by /u/yannisassael [link] [comments]

I work as a Computer Vision engineer, working mostly with classification and object detection problems. Work is quite demanding so whatever time I get, I try to search for new stuff happening in Computer Vision/Deep Learning space. I usually rely on LinkedIn, Twitter and Reddit. At times I find good stuff while scrolling but not always. I really want few fixed sources (3-4 sites maybe?) which keeps me somewhat up to date in this space. I know it's very difficult to stay 100% upto date. Also, not limiting the space to only classification and object detection, it can be any area in Computer Vision (Zero shot learning, new Optimizers, survey papers, LLM + CV, etc) Few sources I refer to apart from above (not very regular though) Papers with code Arxiv Meta/Google blogs Looking for guidance and help 🙏 submitted by /u/Public-Mechanic-5476 [link] [comments]

submitted by /u/Dipanshuz1 [link] [comments]

I work as a Computer Vision engineer, working mostly with classification and object detection problems. Work is quite demanding so whatever time I get, I try to search for new stuff happening in Computer Vision/Deep Learning space. I usually rely on LinkedIn, Twitter and Reddit. At times I find good stuff while scrolling but not always. I really want few fixed sources (3-4 sites maybe?) which keeps me somewhat up to date in this space. I know it's very difficult to stay 100% upto date. Also, not limiting the space to only classification and object detection, it can be any area in Computer Vision (Zero shot learning, new Optimizers, survey papers, LLM + CV, etc) Few sources I refer to apart from above (not very regular though) Papers with code Arxiv Meta/Google blogs Looking for guidance and help 🙏 submitted by /u/Public-Mechanic-5476 [link] [comments]

Hey guys, mew blog post about how to create a a 20-line python script that lets ChatGPT answer questions on any PDF https://medium.com/@pancemarko/talk-to-any-pdf-with-chatgpt-in-20-lines-of-code-66562f1b65bd submitted by /u/mpance_89 [link] [comments]

Expert insights on the latest news are currently locked away from semantic search. We index 1000s hours of audio transcripts and serve 1M+ embeddings across the best podcasts. Devs can route queries for expert opinions to a single API and retrieve the most relevant context. Get started here: Embeddings Playground We're also launching new embeddings every week. If you want to contribute or have ideas for the next drop, we just started a discord. Join us submitted by /u/achyutjoshi [link] [comments]

https://medium.com/@tiago-mesquita/from-algorithms-to-antibiotics-ai-guides-scientists-to-novel-antibiotic-for-drug-resistant-6a902e9e33f6 To develop their computational model, the researchers exposed A. baumannii to around 7,500 chemical compounds in a lab setting. By feeding the structure of each molecule into the model and indicating whether it inhibited bacterial growth, the algorithm learned the chemical features associated with growth suppression. submitted by /u/mesqz [link] [comments]

Hey ya'll, Can you find DS jobs that are more stats focused, and how? Transitioning from academic research to DS, and while I'm good with data manipulation and statistics, we never used NNs in my training and, tbh, I'm not super interested in getting into it right now. I like statistical models, and I feel like there are still a lot of them I want to learn/get a chance to use. submitted by /u/empirical-sadboy [link] [comments]