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    • Scikit Learn

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    101 results for "scikit learn"

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      Coursera Project Network

      Scikit-Learn For Machine Learning Classification Problems

      Skills you'll gain: Data Analysis, Machine Learning

      Beginner · Guided Project · Less Than 2 Hours

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      LearnQuest

      Introduction to Data Science and scikit-learn in Python

      Skills you'll gain: Computer Programming, Python Programming, Statistical Programming, Econometrics, General Statistics, Machine Learning, Probability & Statistics, Advertising, Communication, Data Science, Marketing, Regression

      4.0

      (31 reviews)

      Beginner · Course · 1-4 Weeks

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      Coursera Project Network

      Predict Sales Revenue with scikit-learn

      Skills you'll gain: Applied Machine Learning, Computer Programming, Data Analysis, General Statistics, Machine Learning, Machine Learning Algorithms, Probability & Statistics, Python Programming, Regression, Statistical Programming, Accounting, Data Management, Exploratory Data Analysis, Financial Analysis

      4.5

      (230 reviews)

      Beginner · Guided Project · Less Than 2 Hours

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      Coursera Project Network

      Scikit-Learn to Solve Regression Machine Learning Problems

      Skills you'll gain: Data Analysis, Machine Learning

      Beginner · Guided Project · Less Than 2 Hours

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      Coursera Project Network

      Predict Employee Turnover with scikit-learn

      Skills you'll gain: Data Management, Machine Learning, Machine Learning Algorithms, Theoretical Computer Science, Advertising, Communication, Leadership and Management, Strategy and Operations

      4.4

      (253 reviews)

      Intermediate · Guided Project · Less Than 2 Hours

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      Coursera Project Network

      Multiple Linear Regression with scikit-learn

      Skills you'll gain: Computer Programming, Machine Learning, Machine Learning Algorithms, Probability & Statistics, Python Programming, Regression, Statistical Machine Learning, Statistical Programming

      4.5

      (346 reviews)

      Beginner · Guided Project · Less Than 2 Hours

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      Coursera Project Network

      Perform Sentiment Analysis with scikit-learn

      Skills you'll gain: Machine Learning, Natural Language Processing, Algebra, Data Analysis, Data Science, Python Programming

      4.5

      (407 reviews)

      Intermediate · Guided Project · Less Than 2 Hours

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      Coursera Project Network

      Support Vector Machines with scikit-learn

      Skills you'll gain: Machine Learning, Machine Learning Algorithms, Data Analysis, Data Science, Python Programming

      4.3

      (305 reviews)

      Beginner · Guided Project · Less Than 2 Hours

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      Coursera Project Network

      Linear SVM Classification(Soft Margin) -using Scikit Learn

      Skills you'll gain: Machine Learning

      Intermediate · Guided Project · Less Than 2 Hours

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      Coursera Project Network

      Predict Career Longevity for NBA Rookies using Scikit-learn

      Skills you'll gain: Data Science, Python Programming

      Beginner · Guided Project · Less Than 2 Hours

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      DeepLearning.AI

      Supervised Machine Learning: Regression and Classification

      Skills you'll gain: Machine Learning, Probability & Statistics, Regression, General Statistics, Machine Learning Algorithms, Algorithms, Theoretical Computer Science, Econometrics, Computer Programming, Mathematics, Python Programming, Statistical Machine Learning, Statistical Programming, Applied Machine Learning, Artificial Neural Networks, Calculus, Feature Engineering, Linear Algebra, Probability Distribution, Accounting

      4.9

      (7k reviews)

      Beginner · Course · 1-4 Weeks

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      IBM Skills Network

      IBM AI Engineering

      Skills you'll gain: Machine Learning, Computer Programming, Python Programming, Computer Vision, Deep Learning, Statistical Programming, Artificial Neural Networks, Machine Learning Algorithms, Probability & Statistics, General Statistics, Regression, Applied Machine Learning, Apache, Data Management, Data Mining, Data Analysis, Statistical Analysis, Big Data, Algorithms, Theoretical Computer Science, Statistical Machine Learning, Computer Graphics, Dimensionality Reduction, Tensorflow, Computer Graphic Techniques, Basic Descriptive Statistics, Business Analysis, Correlation And Dependence, Databases, Mathematics, NoSQL, SQL, Estimation, Econometrics, Entrepreneurship, Machine Learning Software, Probability Distribution, Data Science, Data Structures, IBM Cloud, Supply Chain Systems, Supply Chain and Logistics

      4.6

      (15.8k reviews)

      Intermediate · Professional Certificate · 3-6 Months

    Searches related to scikit learn

    scikit-learn for machine learning classification problems
    scikit-learn to solve regression machine learning problems
    predict sales revenue with scikit-learn
    perform sentiment analysis with scikit-learn
    multiple linear regression with scikit-learn
    predict employee turnover with scikit-learn
    support vector machines with scikit-learn
    introduction to data science and scikit-learn in python
    1234…9

    In summary, here are 10 of our most popular scikit learn courses

    • Scikit-Learn For Machine Learning Classification Problems: Coursera Project Network
    • Introduction to Data Science and scikit-learn in Python: LearnQuest
    • Predict Sales Revenue with scikit-learn: Coursera Project Network
    • Scikit-Learn to Solve Regression Machine Learning Problems: Coursera Project Network
    • Predict Employee Turnover with scikit-learn: Coursera Project Network
    • Multiple Linear Regression with scikit-learn: Coursera Project Network
    • Perform Sentiment Analysis with scikit-learn: Coursera Project Network
    • Support Vector Machines with scikit-learn: Coursera Project Network
    • Linear SVM Classification(Soft Margin) -using Scikit Learn: Coursera Project Network
    • Predict Career Longevity for NBA Rookies using Scikit-learn: Coursera Project Network

    Frequently Asked Questions about Scikit Learn

    • Scikit-learn—or skilearn—is a very useful library of algorithms in Python for machine learning. It started out as a Google summer of code project in 2007 then was further developed by a group of data scientists from the French Institute for Research in Computer Science and Automation (FIRCA) and released to the public in 2010. The scikit-learn library lives at a github.com URL and is now a community effort that anyone with qualified skills can contribute to. While the library is primarily written in Python, it's also built on Python-based libraries that include NumPy, Matplotlib, pandas, and SciPy. It gives users tools for statistical modeling and machine learning, such as classification, clustering, regression, model selection, preprocessing, and dimensionality reduction.‎

    • When you learn scikit-learn, you put yourself in a position to be able to contribute to and help maintain the scikit-learn library. Top contributors include data scientists, software developers, machine learning researchers, research scientists, and open-source developers. Outside of contributing to the library, individuals in these career fields and others related to machine learning are better equipped to perform their job duties when they've learned how to utilize the algorithms in scikit-learn.‎

    • Before starting to learn scikit-learn, you should have experience in and a sound understanding of Python. It is also often required to have experience in additional Python libraries, including NumPy, Scipy, Joblib, Matplotlib, and pandas.‎

    • Taking online courses on Coursera can help you learn about Python and machine learning as well as the specifics of using and creating algorithms for scikit-learn. You might learn how to build univariate and multivariate linear regression models using scikit-learn, use pandas to manage data, and perform exploratory data analysis and data visualization with seaborn, a Python library based on Matplotlib. With Coursera's online courses, you may also have the opportunity to make predictions in specific topics like electricity consumption, sentiment analysis, and career longevity for NBA rookies, for example.‎

    This FAQ content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.
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