Welcome to our AI Summer Camp Repo!

Would you like to take the first step towards Deep Learning with a 5-week training in partnership with Google Developers Group?

Make a quick introduction to the field of Deep Learning, which is on the rise today, with 5 different trainings to be given by 5 instructors who are successful in their fields!

This tutorial is for anyone who wants to capture the Artificial Intelligence age on the productive side. Upon completion of this training, you will gain the following competencies:

• You will be able to analyze and solve a basic regression and classification problem using Machine Learning
• You will be able to master artificial neural networks by learning Deep Learning techniques
• You will be able to develop and optimize neural networks by learning the TensorFlow library.
• You will be able to classify images by establishing a Convolutional Neural Network.
• By setting up a Recurrent Neural Network, you will be able to do a basic text classification.
• With all these competencies, you will be prepared for real life and you will be able to take your place in the age of artificial intelligence.

Syllabus

• Week 1: Machine Learning

  • What is Machine Learning?
  • Supervised and Unsupervised Learning
  • Regression and Classification Problems
  • Loss Functions, Optimization Algorithms
  • Desicion Trees

• Week 2: Deep Learning

  • What is Deep Learning?
  • What Deep Learning Accomplished So Far?
  • First Neural Networks
  • Data Representations for Neural Networks
  • Introduction to Keras ve TensorFlow
  • Building Neural Network
  • TensorBoard: TensorFlow Visualization Library

• Week 3: TensorFlow

  • What is Tensorflow?
  • Tensorflow Basics
  • What is Keras?
  • Sequential and Functional Models
  • Training First Model
  • Transfer Learning with Tensorflow

• Week 4: Convolutional Neural Networks (CNN)

  • An in-depth look at the concept of pixel and image
  • Image Preprocesing
  • Image Augmentation
  • Computer Vision and popular areas
  • CNN algorithm and computer vision (how models manipulate an image)
  • Object detection models, comparison, datasets, sample operations

• Week 5: Natural Language Processing (NLP)

  • Why was the Transformer needed?
  • What is Encoder – decoder?
  • What is Attention?
  • What is Self attention?
  • Original Transformer
  • Modern transformer architectures