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Practical Data Analysis - Second Edition
Key FeaturesLearn how to turn data into real insightExplore various concrete examples by mixing data and algorithms to discover the things we don’t know that we don’t knowApply Machine Learning algorithms to different kinds of data such as social networks, time series, and imagesBook DescriptionBeyond buzzwords like Big Data or Data Science, there are a great opportunities to innovate in many businesses using data analysis to get data-driven products. Data analysis involves asking many questions about data in order to discover insights and generate value for a product or a service.
This book explains the basic data algorithms without the theoretical jargon, and you’ll get hands-on turning data into insights using machine learning techniques. We will perform data-driven innovation processing for several types of data such as text, Images, social network graphs, documents, and time series, showing you how to implement large data processing with MongoDB and Apache Spark.
What you will learnAcquire, format, and visualize your dataBuild an image-similarity search engineGenerate meaningful visualizations anyone can understandGet started with analyzing social network graphsFind out how to implement sentiment text analysisInstall data analysis tools such as Pandas, MongoDB, and Apache SparkGet to grips with Apache SparkImplement machine learning algorithms such as classification or forecastingAbout the AuthorHector Cuesta co-founded and is a data-driven product designer at DataNerdsMX, a data science consulting firm in Mexico City. He holds an MSc in Computer Science. He provides consulting services for software engineering and data science and has 10+ years of experience in a variety of industries including financial services, social networking, e-learning, and Human Resources. He is an enthusiast of Lego Robotics and Raspberry Pi and pursues these topics in his spare time.
This book explains the basic data algorithms without the theoretical jargon, and you’ll get hands-on turning data into insights using machine learning techniques. We will perform data-driven innovation processing for several types of data such as text, Images, social network graphs, documents, and time series, showing you how to implement large data processing with MongoDB and Apache Spark.
What you will learnAcquire, format, and visualize your dataBuild an image-similarity search engineGenerate meaningful visualizations anyone can understandGet started with analyzing social network graphsFind out how to implement sentiment text analysisInstall data analysis tools such as Pandas, MongoDB, and Apache SparkGet to grips with Apache SparkImplement machine learning algorithms such as classification or forecastingAbout the AuthorHector Cuesta co-founded and is a data-driven product designer at DataNerdsMX, a data science consulting firm in Mexico City. He holds an MSc in Computer Science. He provides consulting services for software engineering and data science and has 10+ years of experience in a variety of industries including financial services, social networking, e-learning, and Human Resources. He is an enthusiast of Lego Robotics and Raspberry Pi and pursues these topics in his spare time.
486 pages, Kindle Edition
Published September 30, 2016
3 people want to read
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