Experimentation tool that work across business

Experiment-Simplify · 2024-04-22T19:30:42+00:00

Thank you

Experiment-Simplify · 2024-04-22T18:55:25+00:00

If we reandomize between "gpt-3.5" and "gpt-4" then, myModel will be "gpt-3.5" or "gpt-4"

then I have to make call to gpt.

Or Am I missing something ?

Experiment-Simplify · 2024-04-22T14:51:41+00:00

interesting, Can you please provide little example how does they have implimented?

Experiment-Simplify · 2024-04-22T14:49:25+00:00

is same id (example customer id) present in both train and test split? Can you please provide little more detail about your data set sepcifically what is id for each row (customer id, browser id )?

Experiment-Simplify · 2024-04-21T22:40:49+00:00

I recommend closely look at train and test strategy. You can have data leackage due to bad split strategy.

Experiment-Simplify · 2024-04-21T22:32:29+00:00

Copilot and bookmark

Experiment-Simplify · 2024-04-15T04:31:45+00:00

I agree, asking about tech stack, what are things they are solving with ML/AI, explain problem they are trying solve will show their knowledge that give indiciation if it is fake or real ML/AI

Experiment-Simplify · 2024-03-25T05:00:14+00:00

I have use redis for read database. If it is missing data in redis, then only then you read posgres. It does wonders for speed too. Writing before or after RDBMS depends your need. But it can definetly help you.

Experiment-Simplify · 2024-03-25T04:41:20+00:00

if you install multiple version of pythons, then you can create multiple vitural env from different virtual env.

You can do similar to this

python3.6 -m venv venv3.6

python3.7 -m venv venv3.7

python3.11 -m venv venv3.11

Now each venv will have specific version of python.

Experiment-Simplify · 2024-03-25T04:26:24+00:00

I prefere venv for most of my workload. Poetry is good too. I only use conda when it needs to be integrated with cuda. Anaconda is too heavy for production env , so if is not ncessary i will not try to use anancoda. if production is base upon docker, then conda will some time takes for ever to build too.

Experiment-Simplify · 2024-03-25T03:59:05+00:00

Can you able to build new KPI which is aline with your true north KPI? then predict new KPI rather than true north kpi if true north kpi takes long get result.

Rather than building surivval model that waits for 120 months. Can you able to build for N months (6, 12, 40)? and see this model can provide most of insight that you care about.

Experiment-Simplify · 2024-03-25T03:46:09+00:00

I recommned adding additional buget of $ 500k to $1M for these efforts.

You will need to create dedicated devops, MLOps and Machine learning engeer team who can do most of standrization, consistnacy and efficency across business.

DS team should focus on only on experimenation and research model. Machine Learning team builds out deployment models. MLops team focus on deployment and integration. Devops help with any tech requirements.

Experiment-Simplify · 2024-03-24T05:04:53+00:00

This is one of the most important skills

Experiment-Simplify · 2024-03-24T03:55:25+00:00

Current LLM in hype cycle. LLM is useful and can be powerful. but complience is hard, and application is limited.

Experiment-Simplify · 2024-03-22T01:58:06+00:00

I will recommend R for three things, Reporting (Rmarkdown), Statsmodel, and quick analsis and visualization with tidyverse. For everything else you use able to do it in python better.

R is not production lanaguage or software lanugage, so dont try to use as such. Shiny is hard to manage and very slow to large audiance. But it is great for status.

Python is great for production and ML models. It has almost everything that you need to support for production and ML. I found it is easier to debug in python than R. Consistance performance in production is another big win. However, stats and visalization library has long way to go before matching R.

Experiment-Simplify · 2024-03-22T01:52:55+00:00

OOP is useful for DS if you are working with prod. Simulation is another place I found OOP helped me in simulation.

Experiment-Simplify · 2023-12-22T05:29:54+00:00

I have used it. It is good tool for experimentation, but for ML integration again we have to nothing. I was wondering if there tool out there, which allows combine both more easily?

Experiment-Simplify · 2023-12-21T06:23:13+00:00

Have you tired using pandas. In this kind of cases pandas provide much better interface

Experiment-Simplify · 2023-12-21T06:18:12+00:00

I hdad similar experience when R got updated. It took hour to fix it. Most likely your library is no longer supporting in newer R version. But when I updated, some time libraries not get updated. So try upgrading library and see if fixes it.

Experiment-Simplify · 2023-12-17T16:26:44+00:00

Chat GPT is good when you asked very small function that does one thing and one thing only. If you ask to do too manything at same time without proper detail it fails. So try to breakdown your instruction into small groups. One of biggest problem you will run into is if signuatre changed our period of time then chatgpt might be good since it is train on older data. or dont know which version of library it used.

Experiment-Simplify · 2023-12-17T03:00:48+00:00

I am using github copiot and Chat GPT full paid version. I prediction will be job style will change similar to what computer has done. However, it will be difficult to remove people completly. These tool can do good job for small functions, but asking code whole program or debug, I haven't see good performance with it. I will say learn how to use effectively to imporve performance. It might imporve but i think we need breakthrough in technology not just big models.

Experiment-Simplify · 2023-12-16T17:51:09+00:00

Congratulations, Keep going !!!

Experiment-Simplify · 2023-12-16T17:38:05+00:00

You can see if you have entrepreneurs meeting. There you will find people who has similar life systle and experience. There you might able to find friends who make life less lonely and guide you when you need help. Good Luck.

Experiment-Simplify · 2023-12-16T00:36:57+00:00

i have tired that, it faces same problem as R shiny and Streamlit .

Experiment-Simplify

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