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"

  • Skills you'll gain: Interactive Data Visualization, Statistics, Descriptive Statistics, Logistic Regression, Decision Tree Learning, Advanced Analytics, Probability & Statistics, Probability Distribution, Statistical Inference, Applied Machine Learning, Data-Driven Decision-Making, Supervised Learning, Workflow Management, Statistical Methods, Statistical Modeling, Data Cleansing, Data Structures, Interviewing Skills, NumPy, Professional Development

  • Skills you'll gain: Feature Engineering, Decision Tree Learning, Applied Machine Learning, Supervised Learning, Advanced Analytics, Machine Learning, Machine Learning Algorithms, Unsupervised Learning, Analytics, Machine Learning Methods, Random Forest Algorithm, Model Optimization, Model Evaluation, Python Programming, Performance Tuning

  • Skills you'll gain: Data Visualization, Regression Analysis, Advanced Analytics, Analytics, Statistical Analysis, Data Analysis, Applied Machine Learning, Business Analytics, Statistical Methods, Analytical Skills, Data Science, Machine Learning Methods, Artificial Intelligence, Python Programming, Machine Learning

  • From the course: The Nuts and Bolts of Machine Learning

  • From the course: The Nuts and Bolts of Machine Learning·Lesson: PACE in machine learning: The plan and analyze stages

  • From the course: The Nuts and Bolts of Machine Learning

  • From the course: The Nuts and Bolts of Machine Learning·Lesson: Additional supervised learning techniques

  • From the course: The Nuts and Bolts of Machine Learning·Lesson: Course review: The nuts and bolts of machine learning

  • From the course: The Nuts and Bolts of Machine Learning·Lesson: Apply your skills to a workplace scenario

  • From the course: Foundations of Data Science·Lesson: Data career skills

  • From the course: Foundations of Data Science

  • From the course: Clean Your Data·Lesson: The challenge of missing or duplicate data