Machine Learning Python Course
What will I learn?
Mek yu get di páwa fɔ data Ƿith wi Mashin Lɛ́ni Páitɔn Kos, we wi mek spesheli fɔ Biznɛs Intɛlijɛns pɔsin dɛn. Go dip insai data luk-luk ɛn análais, lan gud-gud bɔt aw fɔ pripea data, ɛn yuz ɔl di gud tin dɛn we mashin lɛ́ni algorithm dɛn gɛt lɛk linia rígrɛshɔn ɛn disizhɔn triz. Lan aw fɔ mek ficha, tren mɔdel, ɛn jɔj am, ɛn mek yu mɔdel wok bɛtɛ Ƿith haipárámitá tunin. Fins Ƿith aw fɔ put di mɔdel fɔ wok ɛn raít dɔkyúmɛnteshɔn, fɔ mek shɔ se yu skil dɛn rɛdi fɔ yuz am insai di wok we de go ɔn. Jɔin naw fɔ mek yu BI skil go ap!
Apoia's Unique Features
Develop skills
Enhance your practical skills in the areas listed below.
Lan aw fɔ put mɔdel fɔ wok: Sev, lod, ɛn raít dɔkyúmɛnt bɔt mɔdel dɛn fɔ mek i wok fayn.
Mek ficha ɛnjiniárín go bɛtɛ: Mek intárakshɔn ficha dɛn ɛn pul data insaít dɛn we de sho tɛm.
Mek mɔdel trenín go fayn: Yuz tren-tɛst split ɛn jɔj Ƿith mítrik dɛn.
Luk insai data fayn: Análais data strakchɔ ɛn lod data set yuzin Pándaz.
Mek priprósesín skil dɛn go fayn: Nómalaís, skel, ɛn ínkɔd kátégɔ́rikal data kwik-kwik.
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.