Results for "regularization"
Skills you'll gain: Supervised Learning, Regression Analysis, Applied Machine Learning, Predictive Modeling, Machine Learning, Machine Learning Algorithms, Statistical Modeling, Logistic Regression, Scikit Learn (Machine Learning Library), Model Evaluation, Data Preprocessing, Feature Engineering, Statistical Analysis, Classification Algorithms
Status: Trending in AIDeepLearning.AI
Skills you'll gain: Descriptive Statistics, Bayesian Statistics, Statistical Hypothesis Testing, Probability & Statistics, Sampling (Statistics), Probability Distribution, Linear Algebra, Statistical Inference, A/B Testing, Statistical Analysis, Applied Mathematics, NumPy, Probability, Calculus, Dimensionality Reduction, Numerical Analysis, Mathematical Modeling, Data Preprocessing, Machine Learning, Machine Learning Methods
University of Pittsburgh
Skills you'll gain: Statistical Analysis, NumPy, Probability Distribution, Matplotlib, Statistics, Pandas (Python Package), 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: Linear Algebra, Algebra, Applied Mathematics, Advanced Mathematics, Artificial Intelligence and Machine Learning (AI/ML), Mathematical Modeling, Engineering Analysis, Mathematical Theory & Analysis, Numerical Analysis, Geometry, Data Transformation, Applied Machine Learning, Dimensionality Reduction, Markov Model, Probability
Status: Trending in AIImperial College London
Skills you'll gain: Linear Algebra, Dimensionality Reduction, NumPy, Regression Analysis, Calculus, Applied Mathematics, Data Preprocessing, Unsupervised Learning, Feature Engineering, Machine Learning Algorithms, Jupyter, Advanced Mathematics, Statistics, Artificial Neural Networks, Algorithms, Mathematical Modeling, Python Programming, Derivatives
Johns Hopkins University
Skills you'll gain: PyTorch (Machine Learning Library), Convolutional Neural Networks, Deep Learning, Supervised Learning, Artificial Neural Networks, Model Evaluation, Decision Tree Learning, Network Planning And Design, Machine Learning, Computer Vision
What brings you to Coursera today?
Johns Hopkins University
Skills you'll gain: Responsible AI, Autoencoders, Convolutional Neural Networks, Recurrent Neural Networks (RNNs), Data Ethics, Deep Learning, Artificial Neural Networks, Reinforcement Learning, Generative AI, Generative Adversarial Networks (GANs), Machine Learning Algorithms, Model Deployment, Debugging, Artificial Intelligence, Image Analysis, Unsupervised Learning, Machine Learning Methods, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning, Computer Vision
Skills you'll gain: Convolutional Neural Networks, Model Evaluation, Keras (Neural Network Library), Image Analysis, Deep Learning, Applied Machine Learning, Computer Vision, Dimensionality Reduction, PyTorch (Machine Learning Library), Tensorflow, Machine Learning Methods, Data Preprocessing, Performance Tuning, Artificial Intelligence
DeepLearning.AI
Skills you'll gain: Tensorflow, Deep Learning, Performance Tuning, Machine Learning Methods, Data Preprocessing, Artificial Neural Networks, Model Evaluation, Verification And Validation
Johns Hopkins University
Skills you'll gain: Computer Vision, Model Evaluation, PyTorch (Machine Learning Library), Supervised Learning, Unsupervised Learning, Image Analysis, Applied Machine Learning, Data Preprocessing, Dimensionality Reduction, Reinforcement Learning, Feature Engineering, Machine Learning Algorithms, Convolutional Neural Networks, Regression Analysis, Data Processing, Machine Learning, Data Mining, Data Cleansing, Deep Learning, Artificial Neural Networks
Skills you'll gain: Unsupervised Learning, Supervised Learning, Model Evaluation, Regression Analysis, Scikit Learn (Machine Learning Library), Applied Machine Learning, Predictive Modeling, Machine Learning, Dimensionality Reduction, Decision Tree Learning, Python Programming, Logistic Regression, Classification Algorithms, Feature Engineering
Skills you'll gain: Supervised Learning, Feature Engineering, Applied Machine Learning, Unsupervised Learning, Model Evaluation, Machine Learning Algorithms, Predictive Modeling, Data Preprocessing, Classification Algorithms, Artificial Intelligence and Machine Learning (AI/ML), Dimensionality Reduction, Performance Tuning
In summary, here are 10 of our most popular regularization courses
- Supervised Machine Learning: Regression:Â IBM
- Mathematics for Machine Learning and Data Science:Â DeepLearning.AI
- Mathematical Foundations for Data Science and Analytics:Â University of Pittsburgh
- Linear Algebra from Elementary to Advanced:Â Johns Hopkins University
- Mathematics for Machine Learning:Â Imperial College London
- Mastering Neural Networks and Model Regularization:Â Johns Hopkins University
- Foundations of Neural Networks:Â Johns Hopkins University
- Foundations of Model Optimization and Deep Learning:Â Packt
- Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization:Â DeepLearning.AI
- Applied Machine Learning:Â Johns Hopkins University
