machinelearning
(55)ML systems, production & scaling, execution & collaboration, building for users, conference etiquette.
03 Nov 2024  Ā·  10 min  Ā·  machinelearning engineering production leadership
What to interview for, how to structure the phone screen, interview loop, and debrief, and a few tips.
07 Jul 2024  Ā·  21 min  Ā·  machinelearning career leadership š„
How unit testing machine learning code differs from typical software practices
25 Feb 2024  Ā·  6 min  Ā·  machinelearning engineering python
Sending helpful & engaging pushes, filtering annoying pushes, and finding the frequency sweet spot.
24 Dec 2023  Ā·  18 min  Ā·  teardown recsys machinelearning production
How to use open-source, permissive-use data and collect less labeled samples for our tasks.
05 Nov 2023  Ā·  12 min  Ā·  llm eval machinelearning python
9 patterns including HITL, hard mining, reframing, cascade, data flywheel, business rules layer, and more.
23 Apr 2023  Ā·  20 min  Ā·  machinelearning engineering production recsys
Writing good instructions to achieve high precision and throughput.
12 Mar 2023  Ā·  6 min  Ā·  machinelearning mechanism survey
Collecting ground truth, data augmentation, cascading heuristics and models, and more.
26 Feb 2023  Ā·  16 min  Ā·  teardown machinelearning production
Pilot & copilot, literature review, methodology review, and timeboxing.
22 Jan 2023  Ā·  7 min  Ā·  mechanism machinelearning productivity
Or why I should write fewer integration tests.
04 Sep 2022  Ā·  19 min  Ā·  engineering machinelearning production š©·
Pushing back on the cult of complexity.
14 Aug 2022  Ā·  10 min  Ā·  machinelearning engineering production š„
Understanding and spotting patterns to use code and components as intended.
12 Jun 2022  Ā·  13 min  Ā·  machinelearning engineering python š„
Industry examples, exploration strategies, warm-starting, off-policy evaluation, and more.
08 May 2022  Ā·  14 min  Ā·  teardown recsys machinelearning
Thinking about recsys as interventional vs. observational, and inverse propensity scoring.
10 Apr 2022  Ā·  8 min  Ā·  recsys eval machinelearning
What to consider for in terms of data, roadmap, role, manager, tooling, etc.
13 Feb 2022  Ā·  8 min  Ā·  datascience machinelearning career š„
Beyond getting that starting role, how does one continue growing in the field?
19 Jan 2022  Ā·  6 min  Ā·  learning career machinelearning
Daliana and I had a 2hr chat on all things data science and machine learning.
02 Dec 2021  Ā·  1 min  Ā·  datascience machinelearning career
More than two dozen interviews with ML Practitioners sharing their stories and advice
25 Nov 2021  Ā·  1 min  Ā·  machinelearning career š
Why this is the first rule, some baseline heuristics, and when to move on to machine learning.
19 Sep 2021  Ā·  8 min  Ā·  machinelearning š„
An overview of system design, candidate retrieval, and ranking, with industry examples.
15 Sep 2021  Ā·  1 min  Ā·  recsys machinelearning production
How to generate labels from scratch with semi, active, and weakly supervised learning.
01 Aug 2021  Ā·  12 min  Ā·  teardown machinelearning
Building semantic search; how to calculate recall when relevant documents are unknown.
20 Jul 2021  Ā·  1 min  Ā·  machinelearning š¬
Why real-time RecSys? What does the system design look like in industry? How to build an MVP?
13 Jul 2021  Ā·  1 min  Ā·  recsys machinelearning production
A whirlwind tour of bandits, embedding+MLP, sequences, graph, and user embeddings.
13 Jun 2021  Ā·  25 min  Ā·  teardown recsys machinelearning deeplearning
How to go from knowing machine learning to applying it at work to drive impact.
02 May 2021  Ā·  12 min  Ā·  machinelearning career š©·
An overview and comparison of the various approaches, with examples from industry search systems.
25 Apr 2021  Ā·  21 min  Ā·  teardown machinelearning production š„
Mike and I take a philosophical detour on Talk Python and discuss life lessons from machine learning.
26 Mar 2021  Ā·  1 min  Ā·  machinelearning life
Short vs. long-term gain, incremental vs. disruptive innovation, and resume-driven development.
21 Mar 2021  Ā·  12 min  Ā·  datascience machinelearning leadership
Pointers to think through your methodology and implementation, and the review process.
07 Mar 2021  Ā·  15 min  Ā·  writing machinelearning engineering
Access, serving, integrity, convenience, autopilot; use what you need.
21 Feb 2021  Ā·  19 min  Ā·  teardown machinelearning engineering š„
Design and architecture, tech stack, methodology, results, and lessons learned.
07 Feb 2021  Ā·  5 min  Ā·  machinelearning production
Why real-time? How have China & US companies built them? How to design & build an MVP?
10 Jan 2021  Ā·  21 min  Ā·  teardown machinelearning recsys production š„
Data cleaning, transfer learning, overfitting, ensembling, and more.
22 Nov 2020  Ā·  11 min  Ā·  machinelearning life
A personal take on their deliverables and skills, and what it means for the industry and your team.
08 Nov 2020  Ā·  11 min  Ā·  datascience machinelearning engineering career
Setbacks she faced, overcoming them, and how writing changed her life.
01 Nov 2020  Ā·  11 min  Ā·  career machinelearning writing
Step-by-step walkthrough on the environment, compilers, and installation for ScaNN.
14 Oct 2020  Ā·  3 min  Ā·  python machinelearning til
Checking for correct implementation, expected learned behaviour, and satisfactory performance.
06 Sep 2020  Ā·  14 min  Ā·  machinelearning engineering python
Should I switch from a regex-based to ML-based solution on my application?
04 Sep 2020  Ā·  4 min  Ā·  machinelearning š¬
Why (and why not) be more end-to-end, how to, and Stitch Fix and Netflix's experience
09 Aug 2020  Ā·  17 min  Ā·  datascience machinelearning leadership š„
Part II of the previous write-up, this time on applications and frameworks of Spark in production
05 Jul 2020  Ā·  15 min  Ā·  machinelearning deeplearning production survey
Sharing my notes & practical knowledge from the conference for people who don't have the time.
28 Jun 2020  Ā·  11 min  Ā·  machinelearning deeplearning survey
Can maintaining machine learning in production be easier? I go through some practical tips.
25 May 2020  Ā·  16 min  Ā·  machinelearning engineering production
I thought deploying machine learning was hard. Then I had to maintain multiple systems in prod.
18 May 2020  Ā·  14 min  Ā·  machinelearning engineering production
Comparing baselines (matrix factorization) against novel approaches using graphs & NLP.
14 Jan 2020  Ā·  2 min  Ā·  recsys machinelearning
In-depth sharing on how to put machine learning systems into production.
09 Oct 2019  Ā·  4 min  Ā·  machinelearning production
Keynote on how Asia's tech giants scale and their SuperApp strategy.
03 Oct 2019  Ā·  3 min  Ā·  machinelearning engineering leadership
OMSCS CS7646 (Machine Learning for Trading) - Don't sell your house to trade algorithmically.
11 May 2019  Ā·  9 min  Ā·  omscs learning machinelearning python
How we built an ML system to predict hospitalization costs at admission; sharing at DATAx Conference.
06 Mar 2019  Ā·  4 min  Ā·  production machinelearning
OMSCS CS6601 (Artificial Intelligence) - First, start with the simplest solution, and then add intelligence.
20 Dec 2018  Ā·  8 min  Ā·  omscs learning machinelearning python
OMSCS CS7641 (Machine Learning) - Revisiting the fundamentals and learning new techniques.
27 Dec 2017  Ā·  4 min  Ā·  omscs learning machinelearning python
Or how to put machine learning models into production.
13 Feb 2017  Ā·  8 min  Ā·  machinelearning production python š
Cleaning up text and messing with ascii (urgh!)
11 Dec 2016  Ā·  8 min  Ā·  machinelearning python š
How Lazada ranks products to improve customer experience and conversion at Strata 2016.
09 Dec 2016  Ā·  1 min  Ā·  machinelearning lazada production
Parsing json and formatting product titles and categories.
11 Oct 2016  Ā·  9 min  Ā·  machinelearning python š
Sharing about my first data science competition at DataScience SG.
20 Jun 2015  Ā·  1 min  Ā·  machinelearning
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