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(670) Deep learning has been gradually revolutionizing every field of artificial intelligence, making application development easier. Python Deep Learning Projects imparts all the knowledge needed to implement complex deep learning projects in the field of computational linguistics and computer vision. Each...
Chapter 1, Foundations of Artificial Intelligence Based Systems, covers the basics of how to build smart artificial systems using machine learning, deep learning, and reinforcement learning. We will be discussing various artificial neural networks, including CNNs for image processing purposes and RNNs ...
AItechniquesinthecybersecuritydomaintogenerateCaptchas.Lateryouwilltrainandbuildautonomousvehiclestoself-driveusingreinforcementlearning.YouwillbeusinglibrariesfromthePythonecosystemsuchasTensorFlow,Kerasandmoretobringthecoreaspectsofmachinelearning,deeplearning,andAI.Bytheendofthisbook,youwillbeskilledtobuildyourown...
These datasets can be used for neural networks, deep learning, and machine learning projects: (Includes Stack Overflow datasets) Quandl Python Web Development Projects for Beginners We live to create. What will you create? A great place to get started is to check outFlask tutorialsfor building ...
A curated list of awesome Deep Learning tutorials, projects and communities. - ChristosChristofidis/awesome-deep-learning
Using Anaconda consists of the following: Install miniconda on your computer, by selecting the latest Python version for your operating system. If you already have conda or miniconda installed, you should be able to skip this step and move on to step 2. Create and activate * a new conda en...
facenet is a face recognition system based on deep learning proposed by Google in 2015. It is a multi-purpose recognition system used for face verification, recognition, and clustering. facenet maps face images into a 128-dimensional Euclidean space using a deep convolutional neural network. The ...
ND4J: General purpose linear algebra library with over 500 mathematical, linear algebra and deep learning operations. ND4J is based on the highly-optimized C++ codebase LibND4J that provides CPU (AVX2/512) and GPU (CUDA) support and acceleration by libraries such as OpenBLAS, OneDNN (MKL-DNN)...
The book also highlights how neural networks can be trained using GPU capabilities. You will use popular R libraries and packages—such as MXNetR, H2O, deepnet, and more—to implement the projects. By the end of this book, you will have a better understanding of deep learning concepts and ...