Building Intelligent Recommender Systems, Germany

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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 Germany

The Federal Republic of Germany is the second most populous country in Europe and is located in Central Europe. The official language of the country is German. Germany is one of the richest countries in the world. The main exports of the country include motor vehicles and iron and steel products.

Here are some fun facts about Germany:
The fairy tale writer, the Brothers Grimm, came from Germany and wrote many famous stories such as Cinderella, Snow White, and Sleeping Beauty.
Germany is home to the largest theme park in Europe, the Europa-Park.
The famous composer Ludwig van Beethoven was born in Germany.
The Autobahn, the German highway system, is known for having no general speed limit.

Berlin was divided by the Berlin Wall from 1961 to 1989. Known for its street art, Berlin has many colorful murals and graffiti throughout the city. Also, Berlin is home to many famous museums, such as the Pergamon Museum and the Museum Island. Many clubs and bars stay open until the early hours of the morning in this big city.

Another popular city is Munich, which is famous for its Oktoberfest beer festival that attracts millions of visitors every year. Munich is also home to many historic buildings, including Nymphenburg Palace and the Marienplatz town square.

The country's capital and largest city is Berlin, however Frankfurt is considered to be the business and financial center of Germany. It is home to the Frankfurt Stock Exchange, the European Central Bank, and many other financial institutions. Because of its central location within Europe and its status as a major financial hub, Frankfurt is often referred to as the "Mainhattan," a play on the city's name and its association with the Manhattan financial district in New York City.

Frankfurt is also a major transportation hub, with the largest airport in Germany and one of the largest in Europe, Frankfurt Airport. Additionally, it is a popular destination for tourists, with its historic city center, beautiful parks, and vibrant cultural scene.

Some of the top German technology companies like Siemens AG, Bosch, SAP SE, Deutsche Telekom, Daimler AG and Volkswagen has business centers in Frankfurt. The country has a strong tradition of engineering and innovation, and is home to many other world-class technology companies and research institutions.

Tailored to meet the specific needs of Germany, Bilginç IT Academy combines cutting-edge training methodologies with our comprehensive range of Certification Exam preparation courses and accredited corporate training programs. Experience a transformative approach to IT training that will redefine your expectations.

Building Intelligent Recommender Systems Training in Germany

Assessment type:

Certificate:

Upcoming Trainings

Building Intelligent Recommender Systems Training in Germany

Assessment type:

Certificate:

Prerequisites

What You Will Learn

Outline

Upcoming Trainings