Description

Duration

3 Days

18 CPD hours

This course is intended for

This course is geared for experienced Scala developers who are new to the world of machine learning and are eager to expand their skillset. Professionals such as data engineers, data scientists, and software engineers who want to harness the power of machine learning in their Scala-based projects will greatly benefit from attending. Additionally, team leads and technical managers who oversee Scala development projects and want to integrate machine learning capabilities into their workflows can gain valuable insights from this course

Overview

Working in a hands-on learning environment led by our expert instructor you'll:
Grasp the fundamentals of machine learning and its various categories, empowering you to make informed decisions about which techniques to apply in different situations.
Master the use of Scala-specific tools and libraries, such as Breeze, Saddle, and DeepLearning.scala, allowing you to efficiently process, analyze, and visualize data for machine learning projects.
Develop a strong understanding of supervised and unsupervised learning algorithms, enabling you to confidently choose the right approach for your data and effectively build predictive models
Gain hands-on experience with neural networks and deep learning, equipping you with the know-how to create advanced applications in areas like natural language processing and image recognition.
Explore the world of generative AI and learn how to utilize GPT-Scala for creative text generation tasks, broadening your skill set and making you a more versatile developer.
Conquer the realm of scalable machine learning with Scala, learning the secrets to tackling large-scale data processing and analysis challenges with ease.
Sharpen your skills in model evaluation, validation, and optimization, ensuring that your machine learning models perform reliably and effectively in any situation.

Machine Learning Essentials for Scala Developers is a three-day course designed to provide a solid introduction to the world of machine learning using the Scala language. Throughout the hands-on course, you?ll explore a range of machine learning algorithms and techniques, from supervised and unsupervised learning to neural networks and deep learning, all specifically crafted for Scala developers. Our expert trainer will guide you through real-world, focused hands-on labs designed to help you apply the knowledge you gain in real-world scenarios, giving you the confidence to tackle machine learning challenges in your own projects. You'll dive into innovative tools and libraries such as Breeze, Saddle, DeepLearning.scala, GPT-Scala (and Generative AI with Scala), and TensorFlow-Scala. These cutting-edge resources will enable you to build and deploy machine learning models for a wide range of projects, including data analysis, natural language processing, image recognition and more. Upon completing this course, you'll have the skills required to tackle complex projects and confidently develop intelligent applications. You?ll be able to drive business outcomes, optimize processes, and contribute to innovative projects that leverage the power of data-driven insights and predictions.

Introduction to Machine

Learning and Scala

Learning Outcome: Understand the fundamentals of machine learning and Scala's role in this domain.

What is Machine Learning?

Machine Learning with Scala: Advantages and Use Cases

Supervised Learning in Scala

Learn the basics of supervised learning and how to apply it using Scala.

Supervised Learning: Regression and Classification

Linear Regression in Scala

Logistic Regression in Scala

Unsupervised Learning in Scala

Understand unsupervised learning and how to apply it using Scala.

Unsupervised Learning:Clustering and Dimensionality Reduction

K-means Clustering in Scala

Principal Component Analysis in Scala

Neural Networks and Deep Learning in Scala

Learning Outcome: Learn the basics of neural networks and deep learning with a focus on implementing them in Scala.

Introduction to Neural Networks

Feedforward Neural Networks in Scala

Deep Learning and Convolutional Neural Networks

Introduction to Generative AI and GPT in Scala

Gain a basic understanding of generative AI and GPT, and how to utilize GPT-Scala for natural language tasks.

Generative AI: Overview and Use Cases

Introduction to GPT (Generative Pre-trained Transformer)

GPT-Scala: A Library for GPT in Scala

Reinforcement Learning in Scala

Understand the basics of reinforcement learning and its implementation in Scala.

Introduction to Reinforcement Learning

Q-learning and Value Iteration

Reinforcement Learning with Scala

Time Series Analysis using Scala

Learn time series analysis techniques and how to apply them in Scala.

Introduction to Time Series Analysis

Autoregressive Integrated Moving Average (ARIMA) Models

Time Series Analysis in Scala

Natural Language Processing (NLP) with Scala

Gain an understanding of natural language processing techniques and their application in Scala.

Introduction to NLP: Techniques and Applications

Text Processing and Feature Extraction

NLP Libraries and Tools for Scala

Image Processing and Computer Vision with Scala

Learn image processing techniques and computer vision concepts with a focus on implementing them in Scala.

Introduction to Image Processing and Computer Vision

Feature Extraction and Image Classification

Image Processing Libraries for Scala

Model Evaluation and Validation

Understand the importance of model evaluation and validation, and how to apply these concepts using Scala.

Model Evaluation Metrics

Cross-Validation Techniques

Model Selection and Tuning in Scala

Scalable Machine Learning with Scala

Learn how to handle large-scale machine learning problems using Scala.

Challenges of Large-Scale Machine Learning

Data Partitioning and Parallelization

Distributed Machine Learning with Scala

Machine Learning Deployment and Production

Understand the process of deploying machine learning models into production using Scala.

Deployment Challenges and Best Practices

Model Serialization and Deserialization

Monitoring and Updating Models in Production

Ensemble Learning Techniques in Scala

Discover ensemble learning techniques and their implementation in Scala.

Introduction to Ensemble Learning

Bagging and Boosting Techniques

Implementing Ensemble Models in Scala

Feature Engineering for Machine Learning in Scala

Learn advanced feature engineering techniques to improve machine learning model performance in Scala.

Importance of Feature Engineering in Machine Learning

Feature Scaling and Normalization Techniques

Handling Missing Data and Categorical Features

Advanced Optimization Techniques for Machine Learning

Understand advanced optimization techniques for machine learning models and their application in Scala.

Gradient Descent and Variants

Regularization Techniques (L1 and L2)

Hyperparameter Tuning Strategies

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Machine Learning Essentials for Scala Developers (TTML5506-S)

By Nexus Human

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