Machine Learning r Course
What will I learn?
Sigula amaanyi g'okubangula kompyuta okuyiga (machine learning) n'ekitabo kyaffe ekijjuvu ekya Machine Learning R Course, ekyakolebwa butereevu ku bakugu mu kubala ebitondeko (statistics). Yinga munda mu kuteekateeka data, okumanya obulungi enkola nga okwawula data, okugeraageranya ebintu, n'okukyusa ebintu eby'enjawulo. Ongera okumanya kwo mu kukwata data, okunoonyereza ku data, n'okulongoosa engereso. Yiga okuteeka mu nkola engereso nga Random Forests ne Linear Regression, era ogeze engereso ng'okozesa cross-validation ne metrics nga R-squared. Yimusa obukugu bwo n'ebintu ebikozesebwa eby'omutindo ogwa waggulu ebikoleddwa ku bintu eby'omugaso mu bulamu obwa bulijjo.
Apoia's Unique Features
Develop skills
Strengthen the development of the practical skills listed below
Tegeera obulungi okuteekateeka data: Yawula, geraageranya, era okubisa data mu ngeri entuufu.
Longoosa era okwate data: Yeeza, kebera, era olongoose ebintu ebibula mu R.
Kola EDA: Laga ebintu ebiriwo era okkule ebintu ebyesigama ku buli muntu.
Longoosa engereso: Terera engereso n'okukyusa hyperparameter.
Geeza engereso: Kozesa cross-validation era otegeere metrics z'obukugu.
Suggested summary
Workload: between 4 and 360 hours
Before starting, you can change 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 offers practical and relevant knowledge for your professional journey.