Results for "model+regularization"
Skills you'll gain: Feature Engineering, Applied Machine Learning, Machine Learning Methods, Machine Learning Algorithms, Deep Learning, Supervised Learning, Transfer Learning, Model Evaluation, Data Structures, Predictive Modeling, Artificial Intelligence and Machine Learning (AI/ML), Algorithms, Tensorflow, Model Deployment, Machine Learning, Artificial Neural Networks, Performance Tuning, Convolutional Neural Networks, Unsupervised Learning, Data Preprocessing
Status: Top AI ProgramDeepLearning.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
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
Skills you'll gain: Matplotlib, NumPy, Pandas (Python Package), Model Evaluation, Data Preprocessing, Regression Analysis, Scikit Learn (Machine Learning Library), Data Manipulation, Machine Learning, Feature Engineering, Exploratory Data Analysis, Applied Machine Learning, Supervised Learning, Python Programming
Coursera
Skills you'll gain: MLOps (Machine Learning Operations), Data Pipelines, Model Evaluation, Systems Design, Transfer Learning, Data Preprocessing, Data Quality, Feature Engineering, Deep Learning, Python Programming, Data Validation, Scikit Learn (Machine Learning Library), Applied Machine Learning, Predictive Modeling, Software Engineering, Debugging, Supervised Learning, Git (Version Control System), Performance Metric, Statistical Analysis
Skills you'll gain: Generative AI, Generative Model Architectures, Large Language Modeling, LLM Application, Generative Adversarial Networks (GANs), Retrieval-Augmented Generation, OpenAI, Hugging Face, Multimodal Prompts, Responsible AI, Embeddings, Prompt Engineering, AI Security, Autoencoders, Vision Transformer (ViT), Model Deployment, Image Analysis
What brings you to Coursera today?
Skills you'll gain: Model Deployment, Generative AI, AI Workflows, Generative Model Architectures, Development Environment, Image Analysis, Model Evaluation, Performance Tuning, Data Preprocessing
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
Skills you'll gain: Supervised Learning, Data Modeling, Unsupervised Learning, Applied Machine Learning, Data Analysis, Recurrent Neural Networks (RNNs), Model Deployment, Reinforcement Learning, Artificial Intelligence, Classification Algorithms, Classification And Regression Tree (CART), Tensorflow, Machine Learning Algorithms, Keras (Neural Network Library), Artificial Neural Networks, Deep Learning, Machine Learning, Decision Tree Learning, Predictive Analytics, Regression Analysis
Skills you'll gain: MLOps (Machine Learning Operations), Model Evaluation, Applied Machine Learning, Predictive Modeling, Feature Engineering, Workflow Management, Verification And Validation, Business Logic, Machine Learning, Supervised Learning, Statistical Machine Learning, Statistical Modeling, Performance Tuning, Machine Learning Algorithms, Scikit Learn (Machine Learning Library), Benchmarking, Random Forest Algorithm, Performance Analysis, Cost Management, Resource Utilization
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
Skills you'll gain: Model Deployment, Model Evaluation, PyTorch (Machine Learning Library), Transfer Learning, Performance Tuning, Debugging, MLOps (Machine Learning Operations), Deep Learning, Scalability, Artificial Neural Networks
In summary, here are 10 of our most popular model+regularization courses
- Building and Optimizing AI Models :Â Coursera
- Mathematics for Machine Learning and Data Science:Â DeepLearning.AI
- Mastering Neural Networks and Model Regularization:Â Johns Hopkins University
- Learn & Build Machine Learning Models with Python:Â EDUCBA
- ML Model Training & Validation:Â Coursera
- Generative AI and Large Language Models:Â Coursera
- Fine-tuning Image Models with Diffusion:Â Coursera
- Foundations of Model Optimization and Deep Learning:Â Packt
- AI ML with Deep Learning and Supervised Models:Â Simplilearn
- Building, Optimizing, and Validating Machine Learning Models:Â Coursera
