We’ll cowl the next matters on this submit
- Perceive the enterprise downside
- Arrange your working atmosphere and listing format
- Collect knowledge (use multithreading to hurry up 2 to 4x)
- Pre-process knowledge (use vectorization to hurry up 10x)
- Acquire invaluable insights by means of EDA
- Construct interactive visualizations (in Half 2 of this sequence)
- Lastly use ML to reply questions (in Half 3 of this sequence)
- Extras: additionally, you will learn to modularize the code into unbiased and reusable elements, in addition to use abstraction.
Observe: this submit is meant for newbie to mid degree knowledge scientists.
Virtually all knowledge science and ML initiatives begin with a enterprise downside. So, let’s outline the issue that we are attempting to resolve right here first.
Say, you’re employed for a taxi service firm in NYC and your staff is attempting to…