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Machine Learning Essentials for Scala Developers (TTML5506-S)

Name: Machine Learning Essentials for Scala Developers (TTML5506-S)
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Rating: 4.6 (5878 reviews)

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,...

4.6 out of 5 rating
Last updated : 23/07/2026
English

Available as Instructor Led Training, Live Online & In Person at your Offices or Ours.

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Download Overview

Duration:

24.00 hours

19.5 CPD hours

Overview:

Description:

Discover the power of machine learning with Scala, a versatile and high-performance programming language perfect for
handling large-scale data processing and analysis. Put your Scala skills to work learning how to build intelligent applications and solve complex problems across various domains®®without the need for deep mathematical expertise.
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.

Course Outline:

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
Lab: Setting up your environment (OPTIONAL)
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
Lab: Linear Regression Model
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
Lab: K-means Clustering: Apply K-means clustering to a dataset in Scala using Breeze.
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
Lab: Feedforward Neural Network: Build a simple feedforward neural network in Scala using DeepLearning.scala.
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
Lab: Text Generation with GPT-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
Lab: Q-learning in Scala: Implement a simple Q-learning algorithm in Scala to solve a gridworld problem.
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
Lab: Time Series Forecasting: Perform time series forecasting using Scala with an ARIMA model.
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
Lab: Text Classification in Scala: Description: Implement a text classification model in Scala using Breeze and Saddle.
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
Lab: Image Classification in 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
Lab: Model Evaluation 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
Lab: Parallelized Machine Learning: Implement a parallelized version of a machine learning algorithm in 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
Lab: Model Deployment with Scala
Addendum: Next Steps in Machine Learning with Scala

Bonus Chapters / Time Permitting

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
Lab: Implementing a Random Forest model
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
Lab: Feature Selection and Transformation
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
Lab: Hyperparameter Tuning with Grid Search

Available Delivery Options for Machine Learning Essentials for Scala Developers (TTML5506-S)

Live Instructor Led Classroom Online (Live Online)
Traditional Instructor Led Classroom training (TILT/ILT)
Delivery at your offices in United Kingdom
Private dedicated course for your staff

How many CPD hours does Machine Learning Essentials for Scala Developers (TTML5506-S) provide?

The 3 day Machine Learning Essentials for Scala Developers (TTML5506-S) course gives you up to 19.5 CPD hours/structured learning hours.

Who is the correct audience for Machine Learning Essentials for Scala Developers (TTML5506-S)?

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.

Do you provide training for Machine Learning Essentials for Scala Developers (TTML5506-S)?

Yes, we provide corporate training, dedicated training and closed classes for Machine Learning Essentials for Scala Developers (TTML5506-S). This can take place anywhere in United Kingdom including London, Manchester, Birmingham, Edinburgh or live online.

What is the duration of Machine Learning Essentials for Scala Developers (TTML5506-S)?

The Machine Learning Essentials for Scala Developers (TTML5506-S) training takes place over 3 day(s), with each day lasting approximately 24.00 hours including breaks.

What other terms do people search for?

Popular related searches include: Scala; Machine Learning

Why are Nexus Human the best provider for Machine Learning Essentials for Scala Developers (TTML5506-S)?

Nexus Human are recognised as one of the best training companies. Our trainers have won awards including Small Firms Best Trainer, national training partner of the year for Ireland, and global top 30 instructor awards in 2012, 2019 and 2021.

Is there a discount code for Machine Learning Essentials for Scala Developers (TTML5506-S)?

Yes, the discount code PENPAL5 is currently available for Machine Learning Essentials for Scala Developers (TTML5506-S) training. Only one discount code can be used per booking.

DURATION 1 Day

No scheduled classes available at this time.

Training Insurance Included!

When you organise training, we understand that there is a risk that some people may fall ill, become unavailable.

To mitigate the risk we include training insurance for each delegate enrolled on our public schedule, they are welcome to sit on the same Public class within 6 months at no charge, if the case arises.