The Machine Learning With Scala training course will introduce the functional capabilities of the Scala programming language, that are critical to the creation of machine learning algorithms such as dependency injection and implicits. Delegates start by learning data preprocessing and filtering techniques. Following this, they will move on to unsupervised learning techniques such as clustering and dimension reduction, followed by probabilistic graphical models such as Naive Bayes, hidden Markov models and Monte Carlo inference. Further, it covers the discriminative algorithms such as linear, logistic regression with regularization, kernelization, support vector machines, neural networks, and deep learning.
By attending Machine Learning With Scala workshop, delegates will learn to:
- Build dynamic workflows for scientific computing
- Leverage open source libraries to extract patterns from time series
- Master probabilistic models for sequential data
- Dive into neural networks and some deep learning architecture
- Apply some basic multi armed-bandit algorithms
- Analyze and implement linear regression and GLMs in Scala and run them on real datasets
- Use the Naive Bayes algorithms and its methods to predict the probability of different classes based on various attributes
If you are a data scientist or a data analyst with a fundamental knowledge of Scala who wants to learn and implement various Machine learning techniques, this course is for you. All you need is a good understanding of the Scala programming language, a basic knowledge of statistics, a keen interest in Big Data processing.