Posts tagged graident boosted algorithms
Keep Analytics, Machine Learning, and Artificial Intelligence to Simple Use-Cases with Collective Vantage
Keep Analytics, Machine Learning, and Artificial Intelligence to Simple Use-Cases with Collective Vantage

Conaxon takes the reader through a simple sales forecasting project for a retail store. We cover data cleaning (pandas), feature engineering (encoding categorical/cyclical features), building a base GradientBoostedRegressor Model (Sklearn), and hyper-parameter tuning (GridSearchCV, RandomizedSearchCV, KFold).

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ArticlesTyler BetthauserConaxon LLCSklearn, graident boosted algorithms, GradientBoostedRegressor, gridsearchcv, RandomizedSearchCV, Sales Forecast, Random Forest, Encoding, MinMaxScaler, Pandas, seaborn, matplotlib, hyper-parameter tuning, Machine Learning, artificial intelligence, Business Intelligence, Small Business, Micro Business, Collective Vantage
Predict which Sales Leads Close Part 1
Predict which Sales Leads Close Part 1

Can you predict which leads you might close? We propose a simple project to demonstrate a machine learning use case for optimizing which leads sales teams are predicted to be closed.

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ArticlesTyler BetthauserConaxon LLCAnalytics, Machine Learning, Data Science, Sci-Kit Learn, Decision Intelligence, Decision Trees, Support Vector Machine (SVC), train test split, graident boosted algorithms, Olist, Kaggle, Exploratory Data Analysis, Python, How-to, Sales Funnel, Marketing Funnel, Sales Prediction, Qualified Leads, Whitepaper