Mathematics For Machine Learning Course
What will I learn?
Imarisha ujuzi wako wa Akili Bandia ya Biashara (Business Intelligence) na kozi yetu ya Hisabati kwa Mafunzo ya Mashine. Ingia ndani kabisa ya uchunguzi wa data, ukifahamu mbinu za kugundua data iliyo kinyume na kanuni (outliers) na kushughulikia data ambayo haipo (missing values). Jifunze uchakataji wa data (data preprocessing), ikiwa ni pamoja na usawazishaji (normalization) na utatuzi wa data iliyo kinyume na kanuni, ili kuongeza usahihi wa modeli. Chunguza algoriti za mafunzo ya mashine kwa mfuatano wa nyakati (time series), kama vile miti ya maamuzi (decision trees) na ARIMA. Pata utaalamu katika uhandisi wa vipengele (feature engineering), mbinu za uboreshaji (optimization techniques), na tathmini ya modeli (model evaluation). Kozi hii inakupa ujuzi wa kivitendo na wa hali ya juu kwa matumizi ya ulimwengu halisi.
Apoia's Unique Features
Develop skills
Enhance the practical skills outlined below
Fahamu miundo ya data: Changanua na ufsiri seti tata za data kwa ufanisi.
Gundua data iliyo kinyume na kanuni: Tambua hitilafu ili kuongeza usahihi na uaminifu wa data.
Tumia modeli za mfuatano wa nyakati: Tumia ARIMA na LSTM kwa utabiri sahihi.
Boresha algoriti: Tekeleza gradient descent kwa mafunzo bora ya modeli.
Unda vipengele: Tengeneza vipengele vya polynomial ili kuboresha utendaji wa modeli.
Suggested summary
Workload: between 4 and 360 hours
Before beginning, you can adjust chapters and the workload.
- Choose which chapter to start with
- Add or remove chapters
- Adjust 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 program, but offers practical and relevant knowledge for your professional journey.