BigML Analyst : we believe that best way to add business value is by showing and not just telling what is possible i.e. Machine Learning techniques.
– Understand what Machine Learning is, the many different Machine Learning applications across industries, and what tasks can be performed to solve a given business problem according to the data you have.
– Learn how to train your own Machine Learning models and make predictions with them using the BigML Dashboard.
– No prior experience in Machine Learning is required to enroll in this course.
1. Introduction to Machine Learning
a). Introduction to Machine Learning
b). Machine Learning use cases and real-world applications
c). BigML sources and datasets
d). Supervised learning models: Models, Ensembles, Linear Regressions, Logistic Regressions, Deepnets, Time Series, OptiML, and Fusions
f). Evaluations: How to properly evaluate a predictive model
g). Unsupervised learning models: Clusters, Anomaly Detectors, Associations, and Topic Models
2. Data Preparation for Machine Learning with BigML Analyst
a). Data processing for Machine Learning
b). ML-ready data
c). Feature engineering
d). Feature selection
3. Automating Machine Learning in 1-Click of BigML
a). Machine Learning iterations
b). Real Machine Learning solutions requirements
c). 1-click automation: Scriptify