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blog.insightdatascience.com
Company blog · blog.insightdatascience.comdatacareer
blog.insightdatascience.com is the company blog at blog.insightdatascience.com, writing about data and career. Since 2016, 52 different Hacker News readers have linked it 175 times, most often “Always start with a stupid model, no exceptions”. No feed was found, so read it on the site itself.
Too few sampled comments (11) to say how often HN recommends it.?
Why HN links it
HN readers link Insight Data Science posts on practical NLP and ML, data science versus data engineering, career transition to ML roles, and tutorials for search, embeddings and Hadoop-based pipelines.
Summarised by Claude from a sample of 11 HN comments that link here. Each comment is marked recommending, critical or neutral (citing without judging); how this works.
Most-linked posts?
- Always start with a stupid model, no exceptions3 people · 5 mentions · first linked 2018-03-06
- How to build your own CDN with Kubernetes3 people · 3 mentions · first linked 2019-03-25
- Heart Disease Diagnosis with Deep Learning3 people · 3 mentions · first linked 2017-09-12
- “The Unreasonable Effectiveness of Deep Learning Representations”2 people · 4 mentions · first linked 2018-07-05
- ElastiK Nearest Neighbors Online Search Engine2 people · 3 mentions · first linked 2018-07-10
- Show HN: Using machine learning to tackle bias in machine learning2 people · 2 mentions · first linked 2019-03-18
- Preparing for the Transition to DevOps Engineering2 people · 2 mentions · first linked 2018-09-19
- Generating custom photo-realistic faces using AI2 people · 2 mentions · first linked 2018-10-25
- How to deliver on Machine Learning projects2 people · 2 mentions · first linked 2018-10-04
- AI at massive scale, and Reinforcement Learning in industry2 people · 2 mentions · first linked 2018-05-08
What Hacker News says?
Hi, Author here, happy to answer questions and share our vision of it. Many problems require more complex approaches, and we definitely have Fellows tackle some of those ( https://blog.insightdatascience.com/entity2vec-dad368c5b830 ). That being said, when it comes to the volume of practical applications that come up for the many teams that we work with, the vast majority can be solved by the techniques outlined in…
Comment linking /entity2vec-dad368c5b830
on “How to solve most NLP problems: a step-by-step guide”Submitted Generating custom photo-realistic faces using AI as a story · 569 points
HN discussionOnline courses recommended in this thread are great resources to get your feet wet. If you want to actually be able to build ML powered applications, or contribute to an MLE team, we've written a blog post which is a distillation of conversations with over 50 top teams (big and small) in the Bay Area. Hope you find it helpful! https://blog.insightdatascience.com/preparing-for-the-transi... Disclaimer: I work for Ins…
Comment linking /preparing-for-the-transition-to-applied-ai-d41e48403447
on “Ask HN: What free resources did you use to learn how to program ML/AI?”Submitted How to solve most NLP problems: a step-by-step guide as a story · 461 points
HN discussionMasters and PhD are required for particular employers. Others not so much but there are caveats. High probability of being the “data” guy who is then made to be the database admin. Better summary at: https://blog.insightdatascience.com/from-phd-to-data-scienti...
Comment linking /from-phd-to-data-scientist-17209c66a9d9
on “Desperate for Data Scientists”Submitted AI for generative design: Plain text to 3D Designs as a story · 239 points
HN discussionAgreed, we've also written about why the best use of your time is to start with a baseline (even in Computer Vision!) https://blog.insightdatascience.com/always-start-with-a-stup...
Comment linking /always-start-with-a-stupid-model-no-exceptions-3a22314b9aaa
on “Lessons for Building AI-Driven Products”Submitted Reinforcement Learning from scratch as a story · 221 points
HN discussionInteresting idea, but seems to very much fall within the category of something you would often want to build in-house. I always imagined the right level of abstraction was closer to spacy's, a framework that lets you easily embed all the things. If you are interested in how to build and use embeddings for search and classification yourself, I wrote a completely open source tutorial here: https://blog.insightdatascie…
Comment linking /the-unreasonable-effectiveness-of-deep-learning-representations-4ce83fc663cf
on “Show HN: Basilica – word2vec for anything”Submitted How to deliver on Machine Learning projects as a story · 162 points
HN discussionI see tons of them. If you're interested in ML, you're probably more looking towards data science. Data engineering (in general) is more about getting the data in a state where it can be used (extracted, cleaned, moved, transformed, etc.) at least from what i've commonly seen in the industry. A decent breakdown is here: https://blog.insightdatascience.com/data-science-vs-data-eng...
Comment linking /data-science-vs-data-engineering-62da7678adaa
on “We’re in the Middle of a Data Engineering Talent Shortage”Submitted Lessons for Building AI-Driven Products as a story · 157 points
HN discussionVery cool, especially the cropping feature! If anybody is curious as to how you would even start to tackle the problem, I wrote a tutorial to build your own prototype here: https://blog.insightdatascience.com/the-unreasonable-effecti...
Comment linking /the-unreasonable-effectiveness-of-deep-learning-representations-4ce83fc663cf
on “New search-by-image method on Bing.com”Submitted Using neural networks to detect car crashes in dashcam footage as a story · 119 points
HN discussionI would recommend first of all that you get familiar with the names and versioning. Hadoop is a mess, and its basically a family of big data projects. You have two/three main components in hadoop: - Data nodes that constitute HDFS. HDFS is Hadoop's distributed file system, which is basically a replicated fs that stores a bunch of bytes. You can have really dumb data (lets say a bunch of bytes), compressed data (whic…
Comment linking /spinning-up-a-free-hadoop-cluster-step-by-step-c406d56bae42
on “Ask HN: Best way to start and master Hadoop?”Submitted A Newbie’s Guide to Cassandra as a story · 119 points
HN discussionHere's a complete tutorial--from concepts to step-by-step command-line scripting. Eg, you provision EC2 instances, deploy a Hadoop cluster, and build a simple data processing pipeline on the cluster. this is intended primarily for data scientists; two mid-level devs in my shop worked through it, and said it was solid. https://blog.insightdatascience.com/introducing-pegasus-one-...
Comment linking /introducing-pegasus-one-does-not-simply-pip-install-hadoop-423f1d521d29
on “Ask HN: How to learn about distributed systems when not possible at work?”Submitted How to build your own CDN with Kubernetes as a story · 114 points
HN discussionA lot of STEM PhD's are transitioning into data science in industry. It seems you have a lot of CS background as well, so "data engineer" might also be a role you should look into. Also, you say you have no experience working with a team. So no collaborations? No co-authors (surely you must have some students working for you)? I see from another comment that you had to go through the tenure process. I'm sure you had…
Comment linking /preparing-for-the-transition-to-data-science-e9194c90b42c?gi=40f8586a4ff0
on “Ask HN: 55 years old and no experience, am I too old to get a job?”Submitted Using Deep Learning to Reconstruct High-Resolution Audio as a story · 114 points
HN discussionBlog post on how this was built: https://blog.insightdatascience.com/elastik-nearest-neighbor...
Comment linking /elastik-nearest-neighbors-4b1f6821bd62
on “Show HN: ElastiKNN – Elasticsearch plugin for scalable image search”Submitted AI vs. Data Science vs. Data Engineering as a story · 97 points
HN discussionSubmitted TensorFlow Image Recognition on a Raspberry Pi as a story · 94 points
HN discussionSubmitted “The Unreasonable Effectiveness of Deep Learning Representations” as a story · 85 points
HN discussionSubmitted Using deep learning to detect malaria in images as a story · 69 points
HN discussionSubmitted Automating breast cancer detection with deep learning as a story · 65 points
HN discussionSubmitted Build a scalable, online recommender with Keras, Docker, GCP, and GKE as a story · 60 points
HN discussionSubmitted New York City: Data Science’s Best Bet for Growth and Opportunity as a story · 56 points
HN discussionSubmitted Using Data Science to Help Women Make Contraceptive Choices as a story · 47 points
HN discussionSubmitted Building a Slack bot for channel topic detection using word embeddings as a story · 39 points
HN discussion
