This service focuses on machine learning implementation from writing scripts, pipelines and automation.
Data preparation:
This is where data is prepared for analysis and machine learning models. This stage involves data reorganization, encoding, feature engineering, dimension reduction etc
Modelling
Choosing the right model and algorithm is a crucial stage. Several models can be trained and tested and the best model is selected based on various evaluation metrics like accuracy, MSE, recall and precision etc.
some of the machine learning algorithms we can implement.
RANDOM FOREST, DECISION TREES, XGBOOST,GBM, LIGHT GBM, ADABOOST, RECUCURRENT NEURAL NETWORK, K-NEAREST NEIGHBOUR
Machine learning standalone apps and automation
Quite often you would like these models to perform predictions or trigger some actions when certain conditions are met. Pipelines and automation APIs come in handy here.
Tools
PYTHON,RStudio ,APACHE AIRFLOW, KERAS, PYSPARK,PIPE, THINKER, HEROKU,