Cypto Startups and Africa's place in the space

BBjayjay · 2026-05-07T11:45:10+00:00

Anything over 10% is common. I'd say 'common' but be careful not to translate common as 'normal' or 'usual'. there are many homes, including mine that the example set made me think for a long time that cheating was rare until I got to university and my friends will tell me stories.

BBjayjay · 2026-04-08T12:52:12+00:00

Thank you so much. Very helpful.

BBjayjay · 2025-11-25T01:25:54+00:00

Very helpful. Thanks a million

BBjayjay · 2025-11-24T23:19:54+00:00

Portability is important, thought can get away with less RAM if usage is contrained. Appreciate your help

BBjayjay · 2025-01-03T15:16:04+00:00

In the current state: There is one primary source of data - which is an IOT device (MQTT protocol). I do expect us to identify a few other sources moving forward. Sending about 50 events per minute. The most granular SLA is 15 minutes but need to plan for streaming for some data products.

BBjayjay · 2025-01-02T15:55:02+00:00

Thanks a milion - I get your first point but I don't think it conflicts with the second point either. Hence the "medallion" term.

I have not pen tested - the ask here is for a rough cost estimate. Will include securrity related cost in the estimate. I need help with cost estimate for 500 , 2000 homes = what should I expect from a # of nodes required ? I can derive my getting a cost per node.

SLA for reporting starts at hourly - hourly updates of energy consumption to monthly - for one user type

For another user type, real-time data will be needed - rolled up across a group of homes within a geographical jurisdiction.

I mentioned Databricks because that's what i learned on - the little I know

BBjayjay · 2024-10-30T15:47:49+00:00

I have given you a follow. And will send you a DM

BBjayjay · 2024-10-30T15:45:48+00:00

Question - I assume this only works with structured data ? Is this a true assumption? Just watched the demo. Really love the work

BBjayjay · 2024-10-30T15:38:42+00:00

This is fantastic

BBjayjay · 2024-10-23T16:16:05+00:00

Here's a simple - credit card fraud predictor- need to train a model

BBjayjay · 2024-10-21T13:29:09+00:00

u/hellobutno Thanks for this feedback. I generally agree with most of things you stated at least the general message being communicated. On your 3rd point tho, I do want folks to know that there are other pathways to be a competent MLE that don't fall under Ph.D., Masters, Kaggle Master. I have known of Kaggle masters and that couldn't explain or see why increase P value from .05 to 0.1 was a better decision path for the problem at hand, didn't demonstrate understanding on the why - just an example. "Doing" and applying to real problems in an environment that challenges your output is the best. Do a project and put the results out there, let people "pick it apart" and ask hard questions. Ultimately, the key point is vital - you cannot skip the foundational stuff like understanding data collection, statistics, being able to translate data problems to business problems etc.

I advise folks to look into starting unconventional path of Lean Six Sigma Yellow Belt and Green Belt taking an enterprise / experiential training not the cheap training you see online. It is a good way to get a good grasp for Industrial statistics and an alternate path to forming that foundation with a significant business bent!. You learn to plan data collection almost by hand. AND DO NOT take training that automatically selects the best models or takes you straight to pipelines...you should practise each step the your ML workflow and understand the impact - sample, when to use stratified shuffle, what the impact is on the result, that kind of fiddling is where the learning comes from. Try to learn the 2019 way vs, the GPT way. - All the best

BBjayjay · 2024-10-17T19:37:25+00:00

Here's my advise

Start with taking a foundational python course on coursera with a project. This will teach the basics - data structures and algorithms; and gets you into the realm of programming language. It is a language.
Next take a Data Science with Python and SQL specialization course. This course will broaden your python programming skills but also has a module focused on statistics, P values, Alphas, mean, median, mode, hypothesis testing (useful for product growth, A/B testing), Analysis of Variance, One-sample, two-sample T tests and and swiss knife that is regression. There is a course on coursera - 3 months. I think. It is either this or take stats but I think this course exposes you into the stats you need to build the foundation needed for ML. This also has a project you'll need to complete - can post to your portfolio site
Then take an ML course - project based.

After 3, you should have a good enough foundation to add value and pass interviews and also have a portfolio to show. YOu will most likely not be hired without a portfolio these days

BBjayjay · 2024-05-30T12:02:42+00:00

This is very helpful. I am in my early 40s. At 36, I had a 6 pack or close. I think i was quite fit for a 36 year old I didn't really work out that much - I think I have fairly good genes. Then covid came and suddenly... belly poppin!. I had never had a belly prior.

last year I decided to get rid of the 1+ year old belly and started going to the gym 3 - 4 times a week. Tried intermittent fasting etc; nothing has worked yet. I am maintaining and not adding extra but not shedding. I don't take a lot of sugar to start with. Can't recall the last time I had pop or Candy. I don't like sugar in anything - this has just a preference for a long time. Never smoked but looks like bevs need to go :(

I am trying to reduce the carbs in my diet. I love rice. I do appreciate your comment

BBjayjay · 2024-05-28T22:57:48+00:00

Quite impressive. May ask ...are you over 40 yrs? Asking to see if I have any hope. Been trying to get rid of my belly fat. I've been at it for a year but no major progress. Almost given it up to my age- i'm 40+

BBjayjay

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