Building Intelligent Recommender Systems, Malta

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Deep learning-based recommender systems are the secret ingredient behind personalized online experiences and powerful decision support tools in retail, entertainment, healthcare, finance, and other industries.

Recommender systems work by understanding the preferences, previous decisions, and other characteristics of many people. For example, recommenders can predict the types of movies an individual will enjoy based on the movies they’ve previously watched and the languages they understand. Training a neural network to generalize this mountain of data and quickly provide specific recommendations for similar individuals or situations requires massive amounts of computation, which can be accelerated dramatically by GPUs. Organizations seeking to provide more delightful user experiences, deeper engagement with their customers, and better informed decisions can realize tremendous value by applying properly designed and trained recommender systems.

This workshop covers the fundamental tools and techniques for building highly effective recommender systems, as well as how to deploy GPU-accelerated solutions for real-time recommendations.

Assessment type:

Skills-based coding assessments evaluate students’ ability to debug and correct production-quality recommendation pipelines.

Certificate:

Upon successful completion of the assessments, participants will receive an NVIDIA Deep Learning Institute certificate to recognize their subject matter competency and support professional career growth

Why Choose NVIDIA Deep Learning Institute for Hands-On Training?

Access workshops from anywhere with just your desktop/laptop computer and an internet connection. Each participant will have access to a fully configured, GPU-accelerated workstation in the cloud.
Obtain hands-on experience with the most widely used, industry-standard software, tools, and frameworks.
Learn to build deep learning and accelerated computing applications for industries, such as healthcare, robotics, manufacturing, accelerated computing, and more.
Gain real-world expertise through content designed in collaboration with industry leaders, such as the Children’s Hospital of Los Angeles, Mayo Clinic, and PwC.
Earn an NVIDIA Deep Learning Institute certificate to demonstrate your subject matter competency and support your career growth.

Intermediate knowledge of Python, including understanding of list comprehension
Data science experience using Python
Familiarity with NumPy and matrix mathematics

Build a content-based recommender system using the open-source cuDF library and Apache Arrow
Construct a collaborative filtering recommender system using alternating least squares (ALS) and CuPy
Design a wide and deep neural network using TensorFlow 2 to create a hybrid recommender system
Optimize performance for both training and inference using large, sparse datasets
Deploy a recommender model as a high-performance web service
Why Choose NVIDIA Deep Learning Institute for Hands-On Training?

Introduction

Meet the instructor.
Create an account at courses.nvidia.com/join

Matrix-Based Recommender Systems
Implement collaborative filtering with singular value decomposition (SVD):

Read sparse data into a GPU using CuPy
Perform ALS efficiently with NumPy broadcasting rules.
Build a content-based filter with cuDF

Training Wide and Deep Recommenders
Build a wide and deep network using TensorFlow 2:

Build a deep network using Keras.
Build a wide and deep network using TensorFlow feature columns.
Efficiently ingest training data with tf.data.
Case study 1: See real-world examples of recommender system model architectures.

Challenges of Deploying Recommendation Systems to Production
Deploy a recommender system in a production environment:

Acquire a trained model configuration for deployment.
Build a container for deployment.
Deploy the trained model using NVIDIA Triton Inference Server.

Final Review

Review key learnings and answer questions.
Learn to build your own training environment from the DLI base environment container.
Complete the assessment and earn a certificate.
Take the workshop survey.
Case study 2: Review real-world challenges of at-scale recommender systems

Building Intelligent Recommender Systems Training Course in Malta

Officially known as the Republic of Malta, is an island country in the Mediterranean Sea, South of Sicily. While Malta being the world's tenth smallest country in area and fourth most densely populated sovereign country, the capital city of the island country is Valletta. Malta consists of three islands: Malta, Gozo, and Comino and Malta is the largest island among all. The official languages of Malta are Maltese and English and based on the data from 2019, the population is about 514,564.

Winter season in Malta is delightfully mild, with temperatures above 12 degrees, so it makes the Maltese Islands a perfect year-round destination. But tourists usually prefer traveling to Malta either in April, May or June. Since in those months, Malta is warm without being too hot. In the early Spring season, travelers may also enjoy the glorious wildflower season.

Enhance your IT skills with our comprehensive array of courses, spanning programming, software development, data science, and project management. Benefit from the convenience of choosing your preferred location in Malta as our experienced instructors deliver interactive training and real-world insights.

Building Intelligent Recommender Systems Training in Malta

Assessment type:

Certificate:

Upcoming Trainings

Building Intelligent Recommender Systems Training in Malta

Assessment type:

Certificate:

Prerequisites

What You Will Learn

Outline

Upcoming Trainings