Bouchlear's repositories
AI-Ressources
Datasets Analysis, pre-trained models, frameworks, cloud services, research papers, courses, libraries, communities, and competitions, providing a comprehensive ecosystem for learning, developing, and advancing AI technologies.
Coding-with-Python
Programming skills are essential in the field of STEM. They play a crucial role in advancing scientific research, technological innovations, engineering solutions, and mathematical problem-solving. Here I will parctice my coding skills in order to develop it through doing exercises and chalenges.
Data-Science-BootCamp
Collection of case study of datasets, exemples of coding and assignements from courses.
Deep-Learning-and-Neural-Network
Case Coding using Deep learning.
IBM-Quantum-Spring-Challenge-2023
This year’s challenge focused on dynamic circuits, a technology that makes it easier to run more-advanced quantum algorithms. Dynamic circuits allow you to include classical processing during the runtime of the circuit
Introduction-to-Quantum-Computing
Introduction to Quantum Computing is an educational resource that provides an overview and foundational understanding of the exciting field of quantum computing. This resource serves as a starting point for individuals interested in exploring the principles, concepts, and applications of quantum computing.
Machine-Learning
Exemples of problems-solving approach that utilizes ML algorithms and statistical models to analyze data, identify patterns, and make predictions or decisions, allowing us to address complex problems across various domains.
QC-for-Quantum-Chemistry
Quantum Simulation of electronic structures and molecular energies can leads to harness in the field of Chemistry.
Quantum-Error-Correction
A set of techniques and algorithms designed to protect quantum information from errors and decoherence, crucial for the reliable implementation of quantum computation and communication.
Quantum-Hardware
Types of qubits and the physical devices and components that are designed and built to perform quantum computation and manipulate quantum information
Quantum-Information-Theory
The fundamental principles and applications of information processing.
Quantum-Maching-Learning
Quantum Machine Learning (QML) refers to the field that explores the intersection of quantum computing and machine learning.
Quantum-Optimization
Quantum algorithms is used to solve optimization problems more efficiently compared to classical methods.
Quantum-Software
The collection of algorithms, programming languages, and tools developed to design, simulate, and execute quantum computations, as well as analyze and interpret the results obtained from quantum hardware devices.
Web-Development
Designing user interfaces, writing code (HTML, CSS, JavaScript, etc.) for websites and applications.