الصفحة 1
الصفحة 1
News bot
The process of gathering and organizing news content has become a challenging task for emerging news sites, necessitating the employment of highly experienced personnel with specialized skills in the field. However, recent advancements in artificial intelligence technology have led to the development of news bots that can efficiently fetch, classify, and rephrase news content from various sources, enabling users to access the latest and well-formulated news without the need for RSS (Really Simple Syndication).
Introduction to Machine Learning with Applications in Information Security
Provides a classroom-tested introduction to a wide variety of machine learning and deep learning algorithms and techniques, reinforced via realistic applications. The book is accessible and doesn't prove theorems, or dwell on mathematical theory. The goal is to present topics at an intuitive level, with just enough detail to clarify the underlying concepts. The book covers core classic machine learning topics in depth, including Hidden Markov Models (HMM), Support Vector Machines (SVM), and clustering. Additional machine learning topics include k-Nearest Neighbor (k-NN), boosting, Random Forests, and Linear Discriminant Analysis (LDA). The fundamental deep learning topics of backpropagation, Convolutional Neural Networks (CNN), Multilayer Perceptrons (MLP), and Recurrent Neural Networks (RNN) are covered in depth. A broad range of advanced deep learning architectures are also presented, including Long Short-Term Memory (LSTM), Generative Adversarial Networks (GAN), Extreme Learning Machines (ELM), Residual Networks (ResNet), Deep Belief Networks (DBN), Bidirectional Encoder Representations from Transformers (BERT), and Word2Vec.
Hearing faces
Our project aims to aid deaf-mute people by tracking hand movements of the deaf-mute person for word level American Sign Language using WLASL model that include 2D CNN -3D CNN and RNN networks training on WLASL large video dataset, then generating the corresponding text and analyzing the person's facial gestures to generate information related to the tone of voice that is most appropriate to the person's age, gender, and race through MTCNN network algorithm that training on generated dataset by us depending on blending VOXCELEB dataset and VGGFACE dataset .
Blind smart helmet
The Smart Helmet for the Blind is a project aimed at providing solutions for the challenges faced by blind individuals in their daily lives. The problem of detecting objects, identifying obstacles and distances, knowing the current location, and using a mobile application is a common issue for blind people. To address these problems, the Smart Helmet project was created, utilizing advanced technology and artificial intelligence to provide real-time assistance to the wearer. The helmet is connected to a Raspberry Pi 4, which processes information from the helmet's cameras and AI algorithms to analyze and predict the surrounding environment for a blind person.
Beginning deep learning with TensorFlow : Work with Keras, MNIST data sets, and advanced neural networks
Stats with an introduction to AI, where you’ll learn the history of neural networks and what sets deep learning apart from other varieties of machine learning. Discovery the variety of deep learning frameworks and set-up a deep learning development environment. Next, you’ll jump into simple classification programs for hand-writing analysis. Once you’ve tackled the basics of deep learning, you move on to TensorFlow 2 specifically. Find out what exactly a Tensor is and how to work with MNIST datasets. Finally, you’ll get into the heavy lifting of programming neural networks and working with a wide variety of neural network types such as GANs and RNNs. Deep Learning is a new area of Machine Learning research widely used in popular applications, such as voice assistant and self-driving cars. Work through the hands-on material in this book and become a TensorFlow programmer! You will: Develop using deep learning algorithms Build deep learning models using TensorFlow 2 Create classification systems and other, practical deep learning applications
