Results for "mathematical foundations for deep learning"
DeepLearning.AI
Skills you'll gain: Descriptive Statistics, Bayesian Statistics, Statistical Hypothesis Testing, Probability & Statistics, Sampling (Statistics), Statistical Methods, Probability Distribution, Linear Algebra, Statistical Inference, Model Optimization, Machine Learning Methods, Statistics, Applied Mathematics, Probability, Calculus, Dimensionality Reduction, Applied Machine Learning, Mathematical Software, Data Transformation, Machine Learning
Imperial College London
Skills you'll gain: Dimensionality Reduction, Linear Algebra, Regression Analysis, NumPy, Calculus, Unsupervised Learning, Applied Mathematics, Statistical Methods, Descriptive Statistics, Model Optimization, Mathematical Software, Jupyter, Statistics, Numerical Analysis, Applied Machine Learning, Geometry, Artificial Neural Networks, Data Science, Data Manipulation, Data Transformation
Skills you'll gain: Computer Vision, Image Analysis, Model Evaluation, Convolutional Neural Networks, Model Optimization, Artificial Neural Networks, Model Training, Machine Learning Methods, PyTorch (Machine Learning Library), Artificial Intelligence and Machine Learning (AI/ML), Deep Learning, Transfer Learning, Machine Learning, Recurrent Neural Networks (RNNs), Artificial Intelligence, NumPy, Python Programming, Matplotlib, Data Visualization, Data Science
University of Pittsburgh
Skills you'll gain: Statistical Analysis, NumPy, Probability Distribution, Matplotlib, Plot (Graphics), Statistics, Data Science, Probability & Statistics, Probability, Statistical Modeling, Predictive Modeling, Data Analysis, Linear Algebra, Predictive Analytics, Statistical Methods, Mathematics and Mathematical Modeling, Applied Mathematics, Python Programming, Machine Learning, Logical Reasoning
Johns Hopkins University
Skills you'll gain: Responsible AI, Autoencoders, Model Training, Convolutional Neural Networks, Recurrent Neural Networks (RNNs), Data Ethics, Model Optimization, Deep Learning, Artificial Neural Networks, Reinforcement Learning, Generative AI, Generative Adversarial Networks (GANs), Machine Learning Algorithms, Model Deployment, Generative Model Architectures, Debugging, Machine Learning Methods, Artificial Intelligence, Image Analysis, Unsupervised Learning
Skills you'll gain: Model Deployment, Deep Learning, Model Optimization, Model Training, Convolutional Neural Networks, PyTorch (Machine Learning Library), Tensorflow, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning Methods, Computer Vision, Recurrent Neural Networks (RNNs), Model Evaluation, Artificial Neural Networks, Natural Language Processing
What brings you to Coursera today?
Johns Hopkins University
Skills you'll gain: Descriptive Statistics, Linear Algebra, Exploratory Data Analysis, Data-Driven Decision-Making, Data Analysis, Bayesian Statistics, Artificial Intelligence, Probability, Regression Analysis, Calculus, Mathematical Software, Advanced Mathematics, Applied Mathematics, Probability Distribution, Mathematical Modeling, Model Optimization, Integral Calculus, Algebra, Machine Learning Algorithms, Dimensionality Reduction
Pearson
Skills you'll gain: Large Language Modeling, Deep Learning, Prompt Engineering, Image Analysis, Model Deployment, Recurrent Neural Networks (RNNs), PyTorch (Machine Learning Library), Convolutional Neural Networks, Model Optimization, Tensorflow, LLM Application, Transfer Learning, Computer Vision, Fine-tuning, Responsible AI, Generative Model Architectures, Model Training, Natural Language Processing, Embeddings, Artificial Neural Networks
Illinois Tech
Skills you'll gain: Recurrent Neural Networks (RNNs), Deep Learning, Generative AI, Convolutional Neural Networks, Transfer Learning, Model Optimization, Image Analysis, Artificial Neural Networks, Generative Model Architectures, Generative Adversarial Networks (GANs), Fine-tuning, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning Methods, Network Architecture, Computer Vision, Network Model, Natural Language Processing, Model Training
MathWorks
Skills you'll gain: Model Evaluation, Computer Vision, Model Deployment, Anomaly Detection, Convolutional Neural Networks, Image Analysis, Transfer Learning, Model Training, Fine-tuning, Deep Learning, Generative AI, Artificial Neural Networks, Applied Machine Learning, Data Preprocessing, Matlab, Software Visualization, Classification Algorithms, Model Optimization, Predictive Modeling, Performance Tuning
Amazon Web Services
Skills you'll gain: Artificial Intelligence and Machine Learning (AI/ML), Generative AI, Deep Learning, Artificial Intelligence, Amazon Web Services, Applied Machine Learning, AI literacy, Machine Learning, Digital Transformation
In summary, here are 10 of our most popular mathematical foundations for deep learning courses
- Mathematics for Machine Learning and Data Science: DeepLearning.AI
- Mathematics for Machine Learning: Imperial College London
- Neural Networks and Computer Vision Foundations: Edureka
- Mathematical Foundations for Data Science and Analytics: University of Pittsburgh
- Foundations of Neural Networks: Johns Hopkins University
- Modern Deep Learning Foundations: Packt
- Foundational Mathematics for AI: Johns Hopkins University
- Learning Deep Learning: Pearson
- Deep Learning: Illinois Tech
- Foundations of Deep Reinforcement Learning with PyTorch: Packt
