Bytes Of Intelligence's repositories
Machine-Learning-Book-Collections
Machine learning is the study and development of data-driven strategies to enhance task performance. AI includes it.
Data-Science-Book-Collections
Data science is an interdisciplinary academic subject that combines statistics, scientific computers, scientific techniques, processes, algorithms, and systems to get information and insights from noisy, structured, and unstructured data.
BytesOfIntelligences
Data Science || Machine Learning || Deep Learning || Computer Vision || NLP Enthusiast Talks about #datascience, #deeplearning, #dataanalytics, #machinelearning, and #machinelearningalgorithms
PyTorch-Developers-Roadmap
PyTorch is an open-source machine learning framework that provides a flexible platform for building, training, and deploying deep learning models. It is widely used for research and development in artificial intelligence, offering dynamic computation, GPU acceleration, and a rich ecosystem of libraries and tools.
TensorFlow-Developers-Roadmap
TensorFlow is an open-source machine learning framework developed by Google. It provides a versatile platform for creating and deploying machine learning models, particularly neural networks, enabling tasks like image recognition, natural language processing, and more.
Artificial-Intelligence-Research-and-Development-Projects
The field of Artificial Intelligence (AI) is a frontier of computer science that focuses on creating systems capable of performing tasks that would typically require human intelligence. This encompasses a wide range of capabilities such as visual perception, speech recognition, decision-making, and language translation.
Fundamentals-of-Computer-Vision-and-Image-Processing
OpenCV (Open Source Computer Vision Library) is an open-source computer vision and machine learning software library. It provides a wide range of tools and functions for various image and video processing tasks.
Comprehensive-exploration-of-various-healthcare-use-cases-through-Python-programming
It covers topics like patient appointment scheduling and notification, medication adherence tracking, emergency room wait time prediction, patient health risk assessment, and health monitoring systems.
Becoming-a-Python-Developer
Becoming a Python developer involves mastering the Python programming language, understanding its syntax, and learning popular frameworks. Gain proficiency in web development, data analysis, or automation. Collaborate on projects, build a strong portfolio, and stay updated on industry trends to excel in this dynamic and versatile field.
Become-Data-Scientist-A-Complete-Roadmap
To become a data scientist, follow these steps: 1. Learn programming (Python, R). 2. Acquire math and statistics skills. 3. Master data analysis and visualization. 4. Study machine learning and deep learning. 5. Gain domain knowledge. 6. Build a portfolio and seek job opportunities.
Data-Science
Statistics is a branch of mathematics that deals with collecting, analyzing, interpreting, presenting, and organizing data. It provides methods to summarize and draw inferences from data, helping to make informed decisions in various fields such as science, business, and government.
Data-Science-Interview-Question-and-Solution
Data Science Interview Question: Explain the concept of regularization in machine learning. Solution: Regularization is a technique to prevent overfitting by adding a penalty term to the loss function.
Machine-Learning-Engineer-Roadmap
A Machine Learning Engineer roadmap typically involves mastering programming languages (Python, R), mathematics (linear algebra, calculus), statistics, and deep learning frameworks (TensorFlow, PyTorch) while gaining practical experience in data preprocessing, model development, and deployment.
Statistics-Roadmap-for-Data-Science-and-Data-Analysis
Statistics is the field of study that involves collecting, organizing, analyzing, interpreting, and presenting data. It plays a crucial role in various disciplines, from science and business to social sciences and healthcare.
Ultimate-Data-Science-Resources
🚀 Welcome to the Unlimited Data Science Resources community! Dive into a wealth of knowledge with curated tutorials, courses, and insights. Elevate your data science journey with boundless learning opportunities! 📊✨
Artificial-Intelligence-Interview-Questions
A "Glossary of Artificial Intelligence" is a concise reference resource defining key terms, concepts, and terminology related to AI. It provides explanations and definitions to help individuals understand and navigate the field of artificial intelligence, making it a valuable tool for both beginners and experts in the AI domain.
Deep-Learning-Engineer-Roadmap
Deep Learning Engineer Roadmap
Fundamentals-of-Physics
Fundamentals of Physics: An Integrated Approach to Projectile Motion, Pendulum Dynamics, Electric Fields, and Thermal Equilibrium
Introductory-Guideline-for-Data-Science-Machine-Learning-Deep-Learning-Image-Processing-Statistics
Welcome to our comprehensive guide on the exciting fields of Data Science, Machine Learning, Deep Learning, Image Processing, Statistics, Natural Language Processing (NLP), and Computer Vision! Let's explore and innovate together!
Data-Science-and-AI-Internship-Program-2024
Join our 2024 Data Science and AI Internship Program at Bytes of Intelligence. Gain practical skills, mentorship, and real-world experience in the dynamic fields of data science and artificial intelligence, preparing you for future success in tech.
Sampling-Methods-in-Statistics-Data-Science-Machine-Learning-and-Deep-Learning
Sampling in statistics involves selecting a subset of individuals from a statistical population to estimate characteristics of the whole population.
Supplemental-Materials
Explore AI with resources like 📚 books, 🎧 podcasts, and 🖥️ online courses! Join forums 💬, attend workshops 🛠️, and read journals 📖 to boost your knowledge! 🚀✨🧠
Supplemental-Materials-For-Deep-Learning-and-AI-Specialization-Course
The Deep Learning and AI Specialization course offered by aiQuest Intelligence provides a comprehensive program designed to teach cutting-edge artificial intelligence, neural networks, and deep learning techniques. This course is aimed at equipping you with the skills needed to tackle real-world AI challenges.
Understanding-Convolutional-Layers
Convolutional layers are a type of neural network layer primarily used in deep learning models for processing data that has a grid-like topology, such as images.
50-Real-World-Use-Case-Based-Python-Function-Practices
50 Real World Use Case Based Python Function Practics
Fundamental-Concepts-and-Architectures-of-Neural-Network
Neural Networks are a set of algorithms, modeled loosely after the human brain, designed to recognize patterns. They interpret sensory data through a kind of machine perception, labeling, and clustering of raw input.