Gentle Introduction To Neural Networks

In this presentation, we will introduce neural networks and take it slowly. We first describe the process of learning machine learning. We will then go into the tools typically involved with machine learning and neural networks. The core of this presentation is taking small steps to achieve a big goal: an understanding of a neural network. This presentation assumes that the audience knows nothing about the internals of machine learning.

• Neural Networks
• Input Layers, Hidden Layers, Output Layers
• Activation Functions
• Cost/Loss Functions
• Backpropagation
• Types of Neural Networks (CNNs, RNNs)
• Common challenges in training neural networks (overfitting, vanishing gradients)
• Where Neural Networks are used? (LLM, image recognition, natural language processing, self-driving cars)
• Tools available and how are they served?
• Ethics in AI

About Daniel Hinojosa

Daniel is a programmer, consultant, instructor, speaker, and recent author. With over 20 years of experience, he does work for private, educational, and government institutions. He is also currently a speaker for No Fluff Just Stuff tour. Daniel loves JVM languages like Java, Groovy, and Scala; but also dabbles with non JVM languages like Haskell, Ruby, Python, LISP, C, C++. He is an avid Pomodoro Technique Practitioner and makes every attempt to learn a new programming language every year. For downtime, he enjoys reading, swimming, Legos, football, and barbecuing.

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