YourPathToDeepLearning
YPDL-Identify-Handwritten-Digits-using-CNN-with-TensorFlow
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YourPathToDeepLearning
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Your Path to Deep Learning
You can access all the workshop resources here: https://github.com/IBMDeveloperMEA/YourPathToDeepLearning/
YPDL-Identify-Handwritten-Digits-using-CNN-with-TensorFlow
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Your Path to Deep Learning
Workshop 2 Resources
What are some alternatives?
YPDL-Recurrent-Neural-Networks-using-TensorFlow-Keras - Build a recurrent neural network using TensorFlow and Keras.
lama - 🦙 LaMa Image Inpainting, Resolution-robust Large Mask Inpainting with Fourier Convolutions, WACV 2022
YPDL-Build-a-movie-recommendation-engine-with-TensorFlow - In this tutorial, we are going to build a Restricted Boltzmann Machine using TensorFlow that will give us recommendations based on movies that have been watched already. The datasets we are going to use are acquired from GroupLens and contains movies, users, and movie ratings by these users.
NST-AI-to-create-art - NST was first introduced in 2015 paper it took advantage of how convolution neural network works to generate art
Real-time-Object-Detection-for-Autonomous-Driving-using-Deep-Learning - My Computer Vision project from my Computer Vision Course (Fall 2020) at Goethe University Frankfurt, Germany. Performance comparison between state-of-the-art Object Detection algorithms YOLO and Faster R-CNN based on the Berkeley DeepDrive (BDD100K) Dataset.
YPDL-SentimentAnalysis-LR - While Deep Learning is a subset of Machine Learning, the prediction methodology in deep learning is different and works similar to how a human brain uses neural pathways to process information & learn from it. In this workshop we will learn about the building blocks of deep learning, neural networks, and how they work. We'll start with Logistic Regression - a simple and basic neural network classification algorithm, having just a one-layer neural network. These are the resources for the first session of Your Path to Deep Learning.