Scikit-learn.org is the official website for Scikit-learn, a Python library for machine learning built on NumPy, SciPy, and matplotlib. As one of the most popular machine learning libraries, Scikit-learn provides various classification, regression, and clustering algorithms, as well as data preprocessing and model selection tools. The website provides documentation and examples on how to use Scikit-learn, including installation instructions, tutorials, and API references. Additionally, Scikit-learn.org provides updates on the latest releases, community-contributed projects, and events related to the library. Overall, Scikit-learn.org is an essential resource for anyone interested in learning or using machine learning in Python.
tutorialspoint.comScikit-learn have sklearn.cluster.SpectralClustering module to perform Spectral clustering.
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EncryptedSite is Encrypted
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CountryHosted in United States
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Latitude\Longitude34.0544 / -118.244 Google Map
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Traffic rank#11,787 Site Rank
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Site age13 yrs old
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Site Owner informationWhois info
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Original author(s)David Cournapeau
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Initial releaseJune 2007
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Stable release1.1.2 / 6 August 2022
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Repositorygithub.com/scikit-learn/scikit-learn
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Written inPython,,,Cython,,,C,and,C++
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Operating systemLinux,,,macOS,,,Windows
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TypeLibrary for,machine learning
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LicenseNew BSD License
#11,787
13 yrs
United States
• Responsible for AI/ML model development and deployment
• Work on a modern AI/ML platform
• Evangelize AI and ML across the company as we make the AI transformation of the company
• Work in a cross functional capacity across all business units including product, marketing, operations, risk, fraud, compliance and finance
• Use every dataset at disposal to build a feature store for AI/ML models as well as a customer 360 profile
• Leverage software engineering best practices for quality, scalability, maintainability and robustness
• Scope and build model monitoring services for the team
Qualifications
• Master’s degree (PhD. Preferred) in a quantitative field such as Decision Science, Data Science, Mathematics, Statistics, Physics, Computer Science, Operations Research or Engineering
• 2-5 years experience with building and deploying ML models into production
• Strong development experience with Python is a must along with ML libraries (pandas, numpy, scikit learn, tensorflow)
• Familiarity with H2O, Azure ML and Amazon Services
• Experience in SQL and database optimization
• Ability to thrive in in a fast paced, team oriented environment
• Experience with deep learning frameworks such as Tensorflow or Pytorch is nice to have
• Experience working in a fintech or finance/banking is nice to have but not required Show more details...
Simplebet is a B2B sports technology company that uses machine learning and real-time solutions to make every moment of every sporting event a betting opportunity. We’re reimagining how people enjoy sports with products that are simple, intuitive, and entertaining. Our technology powers micro-betting capabilities of the leading operators... around the globe.
Simplebet is looking for a Machine Learning Engineer to build and support the machine learning models and infrastructure that power our micro betting experiences. As we grow our business to cover new sports, new betting markets, and new sportsbook partners, you will be integral in ensuring that we are providing our partners with best-in-class sports betting models.
We’ll Trust You To:
• Build machine learning models to predict sports outcomes and power sports betting markets
• Contribute to systems that support the full machine learning lifecycle, including research, iteration, model deployment, low-latency prediction, and model observability
• Design and implement mathematical solutions that enable accurately pricing novel sports betting markets
You’ll Need To Have:
• 4+ years of experience as a Machine Learning Engineer, Data Scientist, or Software Engineer
• Advanced understanding of Python and the machine learning ecosystem in Python (Numpy, Pandas, Scikit-learn, LightGBM, PyTorch, SHAP)
• Strong software engineering skills and experience implementing scalable machine learning solutions in production
• A passion for sports (e.g. NFL, MLB, NBA)
• Strong understanding of statistics and machine learning
Bonus Points For:
• Experience working across data and product teams
• Experience with machine learning observability and explainability
• Experience with Databricks
• Projects involving creative analysis of sports data
• Experience in sports betting
What We Offer:
• Competitive salary, vacation, and equity commensurate to experience
• Health, dental, and vision insurance
• 401k match
• Starting base salary is $150,000, but may vary depending on experience.
Simplebet is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate based upon race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.
We are committed to providing access, equal opportunity and reasonable accommodation for individuals with disabilities in employment, its services, programs, and activities. Please let us know if you require reasonable accommodation for the interview process, and we will make every effort to provide it Show more details...
What you'll do...
About us:
You will join a group focusing on developing data-driven models and services and bringing high quality demand from a wide variety of digital sites (google, bing, facebook, pinterest, etc.) to Walmart E-Commerce sites at low cost in order to sustain and accelerate the growth of Walmart E-Commerce. We also work on ML based customer-centric retention solutions to cultivate a loyal base of omni-channel Wal-Mart customers.
What you’ll do...
• As a machine learning platform team, we are responsible for
• Building and maintaining a robust, scalable machine learning platform for machine learning operations end to end from developing, versioning and deploying machine learning models.
• Developing, deploying, and maintaining high-quality web-based dashboard systems to extract visual insights from an ever-growing dataset, monitor machine learning models, evaluate model performance by A/B test etc.
• Developing, testing, and deploying big-data pipelines and machine learning pipelines from ingestion, model productionization to visualization.
• Building and deploying scalable machine learning API services.
• Managing public cloud services, utilizing public cloud tools and resources efficiently to scale our storage and computation in Google Cloud Platform.
• You will be working as Tech Lead on our backend services for end to end machine learning platform.
We would like you to have…
• Proficiency in at least one programming language, such as python, Java, C++, JavaScript
• Good understanding of data structures and algorithms
• Strong knowledge and experience in big-data techniques, such as spark, hive, spark-sql, noSQL, Big Query, etc.
• Knowledge and experience in Linux, public cloud computing, docker, kubernetes
• Experience in REST API service development
• Experience in machine learning operations and model serving platform will be a plus
Minimum Qualifications...
Outlined below are the required minimum qualifications for this position. If none are listed, there are no minimum qualifications.
Option 1: Bachelors degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 4 years' experience in an analytics related field. Option 2: Masters degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 2 years' experience in an analytics related field. Option 3: 6 years' experience in an analytics or related field
As permitted by applicable law, provide evidence of full vaccination as defined by CDC guidelines OR secure approval of medical or religious accommodation for the vaccination mandate.
Preferred Qualifications...
Outlined below are the optional preferred qualifications for this position. If none are listed, there are no preferred qualifications.
Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, Using open source frameworks (for example, scikit learn, tensorflow, torch Show more details...