Data Science
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What is AI Agent and How its work
AI Agent ek LLM hai jiske paas tools (functions) hote hain. Woh khud decide karta hai ki kaunsa tool chalana hai, result dekhta hai, aur kaam poora hone tak...
Data Science Roadmap, Cheat Sheet aur Interview Questions
Data Science roadmap Hinglish me: aage kya seekhein, Pandas aur scikit-learn cheat sheet, portfolio projects, aur top Data Science interview questions with a...
End-to-End Project: Customer Churn Prediction
End-to-end Data Science project Hinglish me: customer churn prediction — EDA, missing values, ColumnTransformer, Pipeline, Logistic Regression vs Random Fore...
K-Means Clustering: Customer Segmentation
K-Means clustering Hinglish me: unsupervised learning, customer segmentation, scaling, elbow method, silhouette score aur cluster profiles — scikit-learn aur...
Model Evaluation: Confusion Matrix, Precision, Recall aur Cross-Validation
Model evaluation Hinglish me: accuracy paradox, confusion matrix, precision, recall, F1-score, ROC-AUC, k-fold cross-validation aur GridSearchCV hyperparamet...
Decision Tree aur Random Forest
Decision Tree aur Random Forest Hinglish me: tree ke rules dekhna, max_depth aur overfitting, Random Forest ensemble, feature importance — scikit-learn examp...
Logistic Regression: Classification Problems
Logistic Regression Hinglish me: sigmoid function, probability se class, breast cancer dataset pe scikit-learn Pipeline, predict_proba aur threshold badalna...
Linear Regression: Numbers Predict Karna
Linear Regression Hinglish me: best fit line, slope aur intercept, scikit-learn LinearRegression, multiple regression, MAE, RMSE, R² score aur assumptions —...
Feature Engineering: Encoding, Scaling aur Naye Features
Feature engineering Hinglish me: get_dummies, OneHotEncoder, OrdinalEncoder, StandardScaler, MinMaxScaler, date features, pd.cut binning aur data leakage se...