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Results for "técnicas avanzadas en data science, machine learning y deep learning."
DeepLearning.AI
Skills you'll gain: Descriptive Statistics, Bayesian Statistics, Statistical Hypothesis Testing, Probability & Statistics, Sampling (Statistics), Probability Distribution, Probability, Linear Algebra, Statistical Inference, A/B Testing, Statistical Analysis, Applied Mathematics, NumPy, Calculus, Dimensionality Reduction, Machine Learning, Jupyter, Python Programming, Data Manipulation, Data Science
Multiple educators
Skills you'll gain: Unsupervised Learning, Supervised Learning, Artificial Intelligence and Machine Learning (AI/ML), Classification And Regression Tree (CART), Machine Learning Algorithms, Machine Learning, Jupyter, Applied Machine Learning, Data Ethics, Decision Tree Learning, Tensorflow, Scikit Learn (Machine Learning Library), NumPy, Predictive Modeling, Deep Learning, Artificial Intelligence, Reinforcement Learning, Random Forest Algorithm, Feature Engineering, Python Programming
DeepLearning.AI
Skills you'll gain: Computer Vision, Deep Learning, Image Analysis, Natural Language Processing, Artificial Neural Networks, Artificial Intelligence and Machine Learning (AI/ML), Tensorflow, Supervised Learning, Keras (Neural Network Library), Artificial Intelligence, Applied Machine Learning, PyTorch (Machine Learning Library), Machine Learning, Debugging, Performance Tuning, Machine Learning Methods, Python Programming, Data-Driven Decision-Making, Text Mining, Network Architecture
Skills you'll gain: Exploratory Data Analysis, Unsupervised Learning, Supervised Learning, Feature Engineering, Generative AI, Dimensionality Reduction, Reinforcement Learning, Artificial Intelligence and Machine Learning (AI/ML), Data Cleansing, Applied Machine Learning, Data Access, Deep Learning, Data Analysis, Regression Analysis, Machine Learning, Statistical Analysis, Statistical Inference, Machine Learning Algorithms, Classification And Regression Tree (CART), Scikit Learn (Machine Learning Library)
Imperial College London
Skills you'll gain: Linear Algebra, Dimensionality Reduction, NumPy, Regression Analysis, Calculus, Applied Mathematics, Probability & Statistics, Data Transformation, Jupyter, Data Science, Advanced Mathematics, Statistics, Machine Learning Algorithms, Geometry, Statistical Analysis, Machine Learning Methods, Artificial Neural Networks, Algorithms, Data Manipulation, Mathematical Modeling
University of Alberta
Skills you'll gain: Reinforcement Learning, Machine Learning, Sampling (Statistics), Artificial Intelligence and Machine Learning (AI/ML), Artificial Intelligence, Machine Learning Algorithms, Deep Learning, Systems Development, Simulations, Solution Architecture, Markov Model, Supervised Learning, Artificial Neural Networks, Applied Machine Learning, Performance Testing, Algorithms, Statistical Methods, Pseudocode, Linear Algebra, Probability Distribution
Skills you'll gain: Feature Engineering, MLOps (Machine Learning Operations), Google Cloud Platform, Generative AI, Tensorflow, Keras (Neural Network Library), Apache Airflow, Cloud Infrastructure, Artificial Intelligence and Machine Learning (AI/ML), Data Pipelines, Systems Design, Data Management, Data Governance, Hybrid Cloud Computing, Workflow Management, Artificial Intelligence, Application Deployment, Cloud Management, DevOps, Systems Architecture
Skills you'll gain: Jupyter, Automation, Web Scraping, Python Programming, Data Manipulation, Data Import/Export, Scripting, Data Structures, Data Processing, Data Collection, Application Programming Interface (API), Pandas (Python Package), Programming Principles, NumPy, Object Oriented Programming (OOP), Computer Programming
- Status: New
Skills you'll gain: PyTorch (Machine Learning Library), Keras (Neural Network Library), Deep Learning, Reinforcement Learning, Unsupervised Learning, Data Manipulation, Tensorflow, Verification And Validation, Generative AI, Artificial Neural Networks, Data Processing, Predictive Modeling, Applied Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Statistical Methods, Data Import/Export, Artificial Intelligence, Scientific Visualization, Computer Vision, Time Series Analysis and Forecasting
University of Washington
Skills you'll gain: Regression Analysis, Applied Machine Learning, Feature Engineering, Machine Learning, Unsupervised Learning, Artificial Intelligence and Machine Learning (AI/ML), Predictive Modeling, Classification And Regression Tree (CART), Supervised Learning, Bayesian Statistics, Statistical Modeling, Deep Learning, Data Mining, Computer Vision, Statistical Machine Learning, Text Mining, Machine Learning Algorithms, Big Data, Statistical Inference, Data Cleansing
Skills you'll gain: Exploratory Data Analysis, Unsupervised Learning, Supervised Learning, Feature Engineering, Dimensionality Reduction, Data Cleansing, Applied Machine Learning, Data Access, Regression Analysis, Data Analysis, Machine Learning, Statistical Inference, Statistical Hypothesis Testing, Statistical Machine Learning, Data Quality, Machine Learning Algorithms, Classification And Regression Tree (CART), Scikit Learn (Machine Learning Library), Probability & Statistics, Predictive Modeling
Skills you'll gain: Supervised Learning, Feature Engineering, Jupyter, Unsupervised Learning, Scikit Learn (Machine Learning Library), Machine Learning Algorithms, Python Programming, Applied Machine Learning, Statistical Machine Learning, Predictive Modeling, Machine Learning, Dimensionality Reduction, Classification And Regression Tree (CART), Matplotlib, Regression Analysis, Random Forest Algorithm, Statistical Modeling, Data Manipulation
In summary, here are 10 of our most popular técnicas avanzadas en data science, machine learning y deep learning. courses
- Mathematics for Machine Learning and Data Science: DeepLearning.AI
- Machine Learning: DeepLearning.AI
- Deep Learning: DeepLearning.AI
- IBM Machine Learning: IBM
- Mathematics for Machine Learning: Imperial College London
- Reinforcement Learning: University of Alberta
- Preparing for Google Cloud Certification: Machine Learning Engineer: Google Cloud
- Python for Data Science, AI & Development: IBM
- IBM Deep Learning with PyTorch, Keras and Tensorflow: IBM
- Machine Learning: University of Washington