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

    4.6 stars, 8.8K reviews, Intermediate, Course, 1 - 4 Weeks

  • 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

    3.4 stars, 16 reviews, Intermediate, Specialization, 3 - 6 Months

  • EDUCBA

    Skills you'll gain: Computer Vision, Deep Learning, Image Analysis, Convolutional Neural Networks, Exploratory Data Analysis, Feature Engineering, Tensorflow, Model Training, Predictive Modeling, Transfer Learning, Applied Machine Learning, Machine Learning Methods, Application Development, Predictive Analytics, Model Evaluation, Machine Learning, Network Model, Analytics, Network Architecture, Design

    Beginner · Specialization · 1 - 3 Months

  • Board Infinity

    Skills you'll gain: Anomaly Detection, Feature Engineering, Fraud detection, Unsupervised Learning, Continuous Monitoring, Autoencoders, MLOps (Machine Learning Operations), Machine Learning Methods, Statistical Machine Learning, Model Training, Time Series Analysis and Forecasting, System Monitoring, Applied Machine Learning, Model Deployment, Statistical Analysis, Taxonomy

    Beginner · Course · 1 - 4 Weeks

  • 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

    4.9 stars, 39K reviews, Beginner, Specialization, 1 - 3 Months

  • Edureka

    Skills you'll gain: Natural Language Processing, Large Language Modeling, Fine-tuning, Model Evaluation, Recurrent Neural Networks (RNNs), Data Ethics, Responsible AI, Text Mining, Transfer Learning, PyTorch (Machine Learning Library), Artificial Neural Networks, Data Preprocessing, Artificial Intelligence and Machine Learning (AI/ML), Deep Learning, Classification Algorithms, Applied Machine Learning, Data Processing, Machine Learning, Data Analysis, Data Cleansing

    3.1 stars, 8 reviews, Intermediate, Specialization, 3 - 6 Months

  • EDUCBA

    Skills you'll gain: Model Evaluation, Sampling (Statistics), NumPy, Pandas (Python Package), Data Literacy, Feature Engineering, Statistical Visualization, Data Analysis, Predictive Modeling, Analytics, Regression Analysis, Predictive Analytics, Statistics, Analysis, Computational Thinking, Data Science, Business Intelligence, Applied Machine Learning, Data Quality, Machine Learning

    Beginner · Specialization · 3 - 6 Months

  • Coursera

    Skills you'll gain: Generative AI, Model Evaluation, Supervised Learning, Generative Model Architectures, Recurrent Neural Networks (RNNs), Unsupervised Learning, Data Preprocessing, Large Language Modeling, Time Series Analysis and Forecasting, Exploratory Data Analysis, LLM Application, Applied Machine Learning, Data Collection, Model Optimization, Convolutional Neural Networks, Model Deployment, Transfer Learning, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning Methods, Model Training

    4.2 stars, 35 reviews, Intermediate, Professional Certificate, 3 - 6 Months

  • Coursera

    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

    Intermediate · Specialization · 3 - 6 Months

  • Edureka

    Skills you'll gain: Supervised Learning, Computer Vision, Recurrent Neural Networks (RNNs), Machine Learning Methods, Convolutional Neural Networks, Plot (Graphics), Matplotlib, Data Visualization, Probability & Statistics, Deep Learning, AI Personalization, Classification Algorithms, Artificial Intelligence, Plotly, Statistical Analysis, Statistical Methods, Machine Learning, Applied Machine Learning, Digital Signal Processing, Statistical Inference

    3.8 stars, 8 reviews, Intermediate, Specialization, 3 - 6 Months

  • Edureka

    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

    Intermediate · Course · 1 - 4 Weeks

  • DeepLearning.AI

    Skills you'll gain: Model Training, Machine Learning Algorithms, Transfer Learning, Machine Learning, Applied Machine Learning, Data Ethics, Decision Tree Learning, Model Evaluation, Tensorflow, Responsible AI, Supervised Learning, Deep Learning, Classification Algorithms, Random Forest Algorithm, Model Optimization, Artificial Neural Networks, Logistic Regression, Regression Analysis

    4.9 stars, 8.8K reviews, Beginner, Course, 1 - 4 Weeks