Asosiy qismga o'tish

ML Kitob

Baseline dan Neural Network gacha. Leakage, metrikalar, cross-validation, xato tahlili.

48 bob 678 kod bloki 155568 so'z

Mundarija

48 bob
01Yangi dataset: 12 qadam27 kod02ML nima va qachon kerak15 kod03SQL: ma'lumotni bazadan olish20 kod04Vizualizatsiya: ma'lumotni ko'rish14 kod05Ma'lumotni tayyorlash: encoding, missing, scaling20 kod06Train / validation / test va leakage9 kod07Baza (baseline) va birinchi model10 kod08Confusion matrix, precision, recall, F112 kod09ROC, PR, threshold va nomutanosib ma'lumot12 kod10Cross-validation11 kod11Xato tahlili: natija yomon bo'lsa nima qilish14 kod12Vektor va matritsa — ma'lumotning tili14 kod13Cost funksiya va gradient descent16 kod14Normal tenglama va gradient descent12 kod15Linear regression15 kod16Logistic regression12 kod17Regularization: Ridge, Lasso, Elastic Net14 kod18Decision tree (CART)14 kod19Bagging va Random Forest14 kod20Boosting: XGBoost, LightGBM, CatBoost14 kod21KNN va Naive Bayes14 kod22Support Vector Machine (SVM)15 kod23Feature engineering va selection15 kod24Hyperparameter tuning13 kod25Stacking, blending va voting14 kod26SHAP: modelni tushuntirish12 kod27PCA: o'lchovni kamaytirish13 kod28Clustering: K-Means, DBSCAN, hierarchical19 kod29LDA: target ni biladigan o'lchov kamaytirish15 kod30Neyron tarmoq asoslari14 kod31Backpropagation va optimizerlar18 kod32Keras bilan amalda16 kod33PyTorch18 kod34CNN — konvolyutsion neyron tarmoqlar15 kod35RNN, LSTM va vaqt qatorlari14 kod36Attention va Transformer12 kod37O'z ma'lumotingni yig'ish: scraping va API19 kod38Dataset qurish: tozalash, label va split18 kod39Fine-tuning: tayyor modelni moslashtirish15 kod40Modelni saqlash va yuklash17 kod41Django API: modelni xizmatga chiqarish13 kod40Tahrirsiz: titanic bilan birinchi uchrashuv15 kod41Mashq 1: penguins — uchta sinf6 kod42Mashq 2: iflos savdo ma'lumoti7 kod43Mashq 3: yashirin leakage8 kod46Chalkashlik-yechgich16 kod47Intervyu savollari9 kod48Cheat sheet va protokol kartasi9 kod