Applied Machine Learning

Applied Machine Learning is a multidisciplinary approach to constructing algorithms that can learn from and predict future data. Coursera's Applied Machine Learning catalogue provides you with the necessary knowledge and skills to effectively use machine learning in a range of practical applications. You'll learn how to process and analyze large-scale data, build predictive models using supervised and unsupervised learning techniques, and apply these models to real-world problems such as image and speech recognition, autonomous driving, and predictive analytics. Enhance your problem-solving abilities and gain a competitive edge in fields like data science, artificial intelligence, and software engineering by mastering machine learning techniques such as decision trees, neural networks, regression, and clustering.

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Results for "Applied Machine Learning"

  • University of Michigan

    Skills you'll gain: Feature Engineering, Model Evaluation, Applied Machine Learning, Supervised Learning, Scikit Learn (Machine Learning Library), Predictive Modeling, Machine Learning Methods, Machine Learning, Model Training, Model Optimization, Machine Learning Algorithms, Unsupervised Learning, Python Programming, Classification Algorithms, Artificial Neural Networks

  • 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, Machine Learning Methods, Reinforcement Learning, Feature Engineering, Machine Learning Algorithms, Convolutional Neural Networks, Regression Analysis, Data Processing, Model Training, Machine Learning, Deep Learning, Model Optimization

  • Multiple educators

    Skills you'll gain: Unsupervised Learning, Supervised Learning, Model Training, Applied Machine Learning, Machine Learning Algorithms, Transfer Learning, Machine Learning, Jupyter, Data Ethics, Decision Tree Learning, Model Evaluation, Responsible AI, Tensorflow, Scikit Learn (Machine Learning Library), NumPy, Predictive Modeling, Deep Learning, Artificial Intelligence, Classification Algorithms, Reinforcement Learning

  • Skills you'll gain: Model Deployment, Model Optimization, Convolutional Neural Networks, Google Cloud Platform, Natural Language Processing, Tensorflow, MLOps (Machine Learning Operations), Large Language Modeling, Reinforcement Learning, Model Training, Transfer Learning, Computer Vision, Keras (Neural Network Library), Systems Design, Applied Machine Learning, Image Analysis, AI Personalization, Cloud Deployment, Recurrent Neural Networks (RNNs), Machine Learning

  • Status: New

    Skills you'll gain: Supervised Learning, Model Optimization, Feature Engineering, Applied Machine Learning, Unsupervised Learning, Model Evaluation, Machine Learning Methods, Statistical Machine Learning, Machine Learning Algorithms, Predictive Modeling, Model Training, Data Preprocessing, Classification Algorithms, Artificial Intelligence and Machine Learning (AI/ML), Dimensionality Reduction, Data Transformation, Fine-tuning

  • Status: New

    Skills you'll gain: Model Evaluation, Classification Algorithms, Regression Analysis, Data Science, Statistical Modeling, Predictive Modeling, Machine Learning Methods, Exploratory Data Analysis, Machine Learning, Data Analysis, Applied Machine Learning, Machine Learning Software, Feature Engineering, Random Forest Algorithm, Supervised Learning, Logistic Regression, Data Processing, Model Optimization, Data Manipulation, Data Visualization

  • Skills you'll gain: Supervised Learning, Machine Learning Methods, Model Evaluation, Reinforcement Learning, Applied Machine Learning, Statistical Machine Learning, Statistical Methods, Dimensionality Reduction, Unsupervised Learning, Machine Learning Algorithms, Artificial Neural Networks, Statistical Modeling, Decision Tree Learning, Predictive Modeling, Financial Trading, Financial Market, Model Training, Machine Learning, Derivatives, Tensorflow

  • Skills you'll gain: Model Evaluation, Classification Algorithms, Regression Analysis, Matplotlib, Feature Engineering, Time Series Analysis and Forecasting, Data Preprocessing, Jupyter, Image Analysis, Cloud Deployment, Scikit Learn (Machine Learning Library), Applied Machine Learning, Tensorflow, Amazon Web Services, Python Programming, Data Transformation, Logistic Regression, Health Informatics, Machine Learning, Artificial Intelligence and Machine Learning (AI/ML)

  • Status: New

    Skills you'll gain: Model Deployment, Databricks, MLOps (Machine Learning Operations), Cloud Deployment, Feature Engineering, Apache Spark, Model Training, AI Workflows, Machine Learning Software, Data Lakes, CI/CD, Model Evaluation, Applied Machine Learning, Data Store, Machine Learning, Development Environment, Statistical Machine Learning, Data Science, Machine Learning Algorithms, Python Programming

  • Skills you'll gain: Model Evaluation, Applied Machine Learning, Machine Learning Methods, Feature Engineering, Regression Analysis, Machine Learning, Image Analysis, Machine Learning Algorithms, AI Personalization, Model Training, Deep Learning, Transfer Learning, Application Development, Predictive Modeling, Model Deployment, Text Mining, Python Programming, Classification Algorithms

  • Status: New

    Skills you'll gain: Data Preprocessing, Supervised Learning, Model Optimization, Feature Engineering, Pandas (Python Package), Data Wrangling, Exploratory Data Analysis, Data Quality, Model Training, Applied Machine Learning, Data Processing, Data Manipulation, Statistical Machine Learning, Data Transformation, Classification And Regression Tree (CART), Data Cleansing, Data Pipelines, Machine Learning, Data Modeling, Data Architecture

  • Alberta Machine Intelligence Institute

    Skills you'll gain: Supervised Learning, Data Preprocessing, Feature Engineering, Model Optimization, Responsible AI, Machine Learning Algorithms, Data Ethics, Applied Machine Learning, Model Evaluation, Data Quality, Machine Learning Methods, Classification Algorithms, Model Training, MLOps (Machine Learning Operations), Model Deployment, Jupyter, Statistical Machine Learning, Data Validation, Machine Learning, Project Management