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Machine Learning Essentials for Scala Developers (TTML5506-S)

4.6 out of 5 rating

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Duration

3 Days

18 CPD hours

About this course

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.

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 domainswithout 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.

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
Additional course details:

Nexus Humans Machine Learning Essentials for Scala Developers (TTML5506-S) training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward.

This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts.

Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success.

While we feel this is the best course for the ITS Data Analytics course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you.

Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

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.

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