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Introduction to Mathematical Thinking
Mechanics of Materials I: Fundamentals of Stress & Strain and Axial Loading
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Learn Gradient Descent, earn certificates with free online courses from Alexander Amini, Johns Hopkins, Duke, University of Washington and other top universities around the world. Read reviews to decide if a class is right for you.
HMMs for stock price analysis, language modeling, web analytics, biology, and PageRank.
Learn scientific coding in Python from a warm-blooded scientist. Each video includes hands-on solved practice problems!
Learn linear regression from scratch, Statistics, R-Squared, Python, Gradient descent, Deep Learning, Machine Learning
Learn the fundamentals of Deep Learning of neural networks in Python both in theory and practice!
A complete Beginner to Advance level guide to Machine Learning. Hands-on Learning approach with in-depth math concepts
Complete hands-on Machine Learning Course with Data Science, NLP, Deep Learning and Artificial Intelligence
Master practical NLP techniques and their engineering applications through word embeddings, neural networks, and deep learning models. Implement advanced methods for real-world problem-solving in natural language processing.
Understanding Machine Learning for Data Science in python. Best skill to get in free time.
Master deep learning fundamentals through advanced concepts like BERT and T5, using PyTorch and Hugging Face. Hands-on projects progress from basic perceptrons to sophisticated neural networks and transformers.
Explore deep learning and artificial neural networks using TensorFlow. Learn foundational concepts, implement ANN models, and optimize deep learning models through hands-on examples and practical applications.
Master RNNs, GRUs, and LSTMs for deep learning tasks. Build and implement neural networks using TensorFlow, culminating in projects like automatic book writing and stock price prediction.
Master RNN and DNN techniques for AI applications. Build sophisticated models for speech recognition, machine translation, and more using PyTorch. Gain practical skills for real-world AI implementation.
Master Python fundamentals and essential data science skills. Learn data analysis with NumPy and Pandas, explore machine learning concepts, and apply knowledge through practical case studies.
Master RNN architectures and implement sentiment classification models for advanced text analysis and prediction.
Master deep learning with Python: from basics to advanced concepts, hands-on coding, and real-world applications. Gain expertise in neural networks, optimization techniques, and practical implementation through guided tutorials and projects.
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