Presentation: Basics of Deep Learning: No Math Required

Track: Deep Learning Applications & Practices

Location: Cyril Magnin I

Duration: 12:45pm - 12:55pm

Day of week: Wednesday

Level: Beginner

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Abstract

Recently deep learning has shattered all records when it comes to machine learning. Unfortunately, many developers never harness the power of this machine learning technique. In this short talk you will gain a basic understanding of the two most simple types of layers: the dense, and convolutional layer. Take the first steps in your journey to deep learning, no math required.

Note: This is a short talk. Short talks are 10-minute talks designed to offer breadth across the areas of machine learning, artificial intelligence, and data engineering. The short talks are focused on the tools and practices of data science with an eye towards the software engineer.

Speaker: Roland Meertens

Machine Learning Engineer @Autonomous Intelligent Driving

Roland Meertens is Machine Learning Engineer at Autonomous Intelligent Driving. He works on the machine learning side of the perception software stack that will be deployed to the autonomous vehicles that will soon roam urban environments in Germany.

Find Roland Meertens at

Tracks

  • Deep Learning Applications & Practices

    Deep learning lessons using tooling such as Tensorflow & PyTorch, across domains like large-scale cloud-native apps and fintech, and tacking concerns around interpretability of ML models.

  • Predictive Data Pipelines & Architectures

    Best practices for building real-world data pipelines doing interesting things like predictions, recommender systems, fraud prevention, ranking systems, and more.

  • ML in Action

    Applied track demonstrating how to train, score, and handle common machine learning use cases, including heavy concentration in the space of security and fraud

  • Real-world Data Engineering

    Showcasing DataEng tech and highlighting the strengths of each in real-world applications.