Using tools like functional decomposition to enable artificial intelligence, machine learning, and analytics developers in creating better end-to-end solutions
Read MoreConaxon 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).
Read MoreConaxon talks about key problems in applying Machine Learning, Artificial Intelligence, Analytics, and Decision Intelligence within Small / Micro Businesses.
Read Morepropose a simple project to demonstrate a machine learning use case for optimizing which leads sales teams are predicted to be closed.
Read MoreCan 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.
Read MoreTyler, Charles, and Andrew talk about their go-to strategies for how best to wrangle large, unruly data sets to best set your data science project up for success.
Read MoreCharles Elwood, SolisMatica, has me back again with the usual crew to talk careers in analytics and how we think you should approach achieving your goals.
Read More