Python And Machine Learning Course
What will I learn?
Fɛɛ gbɔngbɔng Python Ɔ Machine Learning gbɔngbɔng toh, ná wi wi wi fɔ tɛknɔlɔji pipul. Ɔɔnda gbɛndi insai feature enjiniya stratɛji dem, sabi masta model treniŋ Ɔ ivalueshɔn, Ɔ lukluk data vizualizeshɔn wit Matplotlib. Lan data kolɛkshɔn tiknik dem, priprosesiŋ mɛtɔd dem, Ɔ model silɛkshɔn. Ɛnhans yu skil wit model ɔptimaizeshɔn tiknik dem, inklud hyperparamita tuniŋ Ɔ krɔs-valideshɔn. Dis lensɔn gi yu praktikal, kwaleiti konten fɔ mek yu keeria go op insai tɛk.
Apoia's Unique Features
Develop skills
Enhance your practical skills in the areas listed below.
Masta feature enjiniya: Kriet Ɔ ɔptimaiz data fɛcha fɔ model dem.
ivaluet model dem: Yuz metrik Ɔ valideshɔn fɔ jɔj model pafɔmans.
Du data analises: Vizualiz Ɔ sabi patɛn dem wit Matplotlib.
Priproses data: Klin, nɔmalaiz, Ɔ kia fɔ data we misin gud wan.
Ɔptimaiz algɔritm dem: Tun hyperparamita fɔ model we kɔrɛkt pas.
Suggested summary
Workload: between 4 and 360 hours
Before starting, you can modify the chapters and the workload.
- Choose which chapter to start with
- Add or remove chapters
- Increase or decrease the course workload
Examples of chapters you can add
You will be able to generate more chapters like the examples below
This is a free course, focused on personal and professional development. It is not equivalent to a technical, undergraduate, or postgraduate course, but it offers practical and relevant knowledge for your professional journey.