Weka is a collection of machine learning algorithms for data mining tasks. One can also build hosted products to take away the pain of managing R and RStudio oneself, and allow anyone to use R and RStudio even without serious computing resources. By taking this course, you will form a solid foundation of predictive analytics, which refers to tools and techniques for building statistical or machine learning models to make predictions based on data. Start your predictive analytics journey with these tools Understand and analyze data As the world’s leading statistical analysis software, IBM SPSS® Statistics is designed to solve business and research problems using ad hoc analysis, hypothesis testing, geospatial analysis and predictive analytics. These tools help the user to collect, analyze and mine structured and unstructured data on what has happened before and predict what is likely to happen based on past historical events. It also used Samsara which is a vector math experimentation environment with R-like syntax which works at scale. Facilitating clients to cultivate and develop a social media strategy powered by the latest skills and tools and get the ability to influence the targeted audience while pushing for an increase in sales. For example, to make predictions about what customers are likely to buy in the future, it’s essential to have detailed data on what they have bought in the past to play to their taste, or study their interests and attributes of previously bought items. Twitter Promote Mode: The Pros and Cons and Should You Use it? https://www.youtube.com/watch?v=fw0Vb2gLsgA, • Powerful Analytics • Data & Tool Blending • Open Platform • Over 1000 Modules and Growing •Connectors for all major file formats and databases •Support for a wealth of data types: XML, JSON, images, documents, and many more •Native and in-database data blending & transformation •Math & statistical functions •Advanced predictive and machine learning algorithms •Workflow control •Tool blending for Python, R, SQL, Java, Weka, and many more •Interactive data views & reporting, •Native and in-database data blending & transformation •Math & statistical functions •Advanced predictive and machine learning algorithms, • Churn analysis • Social media sentiment analysis • Credit scoring. TANAGRA is an "open source project" as every researcher can access to the source code, and add his own algorithms, as far as he agrees and conforms to the software distribution license.The main purpose of Tanagra project is to give researchers and students an easy-to-use data mining software, conforming to the present norms of the software development in this domain (especially in the design of its GUI and the way to use it), and allowing to analyse either real or synthetic data. Predicting trends and behaviour patterns become a lot easier. We provide Best Practices, PAT Index™ enabled product reviews and user review comparisons to help IT decision makers such as CEO’s, CIO’s, Directors, and Executives to identify technologies, software, service and strategies. Anaconda is an open data science platform powered by Python. One possibility is Actian Vortex Express (Hadoop SQL Edition), a free graphical community version of Actian's predictive analytics platform running data up to 500 GB on Linux powered by Vortex. Includes the most popular Python, R & Scala packages for stats, data mining, machine learning, deep learning, simulation & optimization, geospatial, text & NLP, graph & network, image analysis. • Bring analytics to your data. What are the Top Predictive Analytics Free Software? GraphLab Create is a machine learning platform to build intelligent, predictive application involving cleaning the data, developing features, training a model, and creating and maintaining a predictive service. MATLAB is another Predictive Analytics Tool used across industry and academia. Data scientists and developers performing broadcasting are also sorted out as NumPy provides detailed and easy to use functions. Dataiku DSS is a collaborative and team-based user interface for data scientists and beginner analysts, to a unified framework for both development and deployment of data projects, and to immediate access to all the features and tools required to design data products from scratch. Platform: Coursera Description: This course will introduce you to some of the most widely used predictive modeling techniques and their core principles. First up on our list of Predictive Analytics Tools is SAS Advanced Analytics. Apache Mahout is a simple and extensible programming environment and framework for building scalable algorithms and contains a wide variety of premade algorithms for Scala and Apache Spark, H2O, Apache Flink. Weka is a collection of machine learning algorithms for data mining tasks. Apache Mahout introduces a new math environment called Samsara, for its theme of universal renewal. Health insurance also needs to analyze vast amounts of data to predict claims fraud and to identify clients most at risk to help them find the best interventions. Weka is written in Java, developed at the University of Waikato, New Zealand. The time from prototyping to production is dramatically reduced for GraphLab Create users. Data mining is done through visual programming or Python scripting. Nonexperts can use the tools to project required reserves to cover a five-year policy, for example, by providing an automated risk profile and liability structure. Spark powers a stack of libraries including SQL and DataFrames, MLlib for machine learning, GraphX, and Spark Streaming. Algorithms: SVM, nearest neighbors, random forest. It then performs analytics – statistical, predictive, and spatial – using the same intuitive user interface, without writing any code. It provides several data mining methods from exploratory data analysis, statistical learning, machine learning and databases area. In the financial sector, the financial institutions need to analyze vast amounts of data to detect and measure fraud, increase cross-sell/upsell opportunities and measure credit risk. Dataiku DSS is the collaborative data science software platform for teams of data scientists, data analysts, and engineers to explore, prototype, build, and deliver their own data products more efficiently. Orange is an open source data visualization and analysis tool, where data mining is done through visual programming or Python scripting. SciPy is an open source software that has a complete collection of features that are used in solving engineering, mathematics and science problems and is also ideal for technical computing and computing scientifically.
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