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Fraud-detection--Insurance
Segmentation-Clustering
Recency, Frequency, and Monetary are three behavioral attributes and are quite simple, in that they can be easily computed for any database that has purchase history, and are easy to comprehend, yet very powerful in their predictive ability.Trading-strategy
Customer-Churn-analysis
Telecom customer churn analysisHistorical-price-index
Predictive AnalyticsMarkov_Model
Markov chains are a classical framework for modeling state and time discrete stochastic systems. It is a sequence of experiments that consists of a finite number of states with some known probabilities (P). P is stochastic process which depends on immediate outcome and not on history.Anomaly_Detection_LSTM_AutoEncoder
ATM-cash-withdrawal-forecast
Stock-Trend-Prediction-with-Technical-Indicators
Mean_Reversion_Trading
Momentum_Trading
Natural-Gas-spot-price-prediction
Forex_VAR-VECM
System-architecture-of-ML-training-platform
ARIMA-Model-for-prediction
ARIMA_Statistical_Model_NaturalGas
LSTM_GRU_CIPLA
Natural-Gas-Prediction-Model
Value_at_Risk
Market-campaign-analytic-Bank
Buy_Sell_Signals
VAR---MoteCarlo_Comparative-analysis
Comparative study of Multiple regression, Monte-Carlo Simulation and ANN in tradingInterest_Rate
BitCoin_hourlyPrediction_Regression
vector-error-correction
Statespace_kalman_schlumberger
VAR_Future-price-prediction_Python
crypto_prediction
traffic_flow_lstm
Prediction-Deploy_pycaret
Credit-rating-bank
Optimizatiion_problem
Price-oscillator-based-break-out-trading
roll_forward_validation
Fraud-investigation-Bank
AZKubernetes-CheatSheet1
PowerBI-script
Python-Fundamentals
ETL-pipeline
mlflow-PetrolConsumption
MLFlow-Keras
StructTS-ARIMA-DLM_Natural-Gas
BacktestingTradingStrategy
GARCH-Processes-Monte-Carlo-Simulations
Bitcoin_prediction_hr_min_daily
Prospect-Response-Propensity-Model
mathews_correlation_coefficient
Local-Explanation-To-Global-Understanding
Regression-Classification-Model-Backtest
This is a sample project for demonstration purpose. ML regression & classification algorithms.ADED
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