Since all of the libraries are open sourced, we have added commits, contributors count and other metrics from Github, which could be served as a proxy metrics for library popularity.
Source: Kdnuggets
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Data science is the theory and practice powering the data-driven transformations we are seeing across industry and society today. Artificial intelligence (AI), self-driving cars, and predictive analytics are just a few of the breakthroughs that have been made thanks to our ever-growing ability to collect and analyze data.
Source: Data Informed15864
Retail investors do not always have adequate time to research opportunities for making money. Fortunately, the rise of big data and artificial intelligence (AI) is helping individual investors make more informed investment choices.
Source: Investopedia9339
The influence and impact of machine learning can be seen in everything from our morning coffee orders to the online banking apps we use.
Source: Datanami8511
So you have developed some base skills in programming, data visualization, data manipulation etc... And are looking for ways to apply those skills and build a data science portfolio?
Source: Datacamp9309
Machine Learning (ML) is coming into its own, with a growing recognition that ML can play a key role in a wide range of critical applications, such as data mining, natural language processing, image recognition, and expert systems.
Source: Toptal17652
Top machine learning writers on Quora give their advice on learning machine learning, including specific resources, quotes, and personal insights, along with some extra nuggets of information.
Source: kdnuggets.54000
Here is a great collection of eBooks written on the topics of Data Science, Business Analytics, Data Mining, Big Data, Machine Learning, Algorithms, Data Science Tools, and Programming Languages for Data Science
Source: Kdnugget52017
These are the most popular data mining books on Amazon. As you look to increase your knowledge, is there something listed here that is missing from your collection?
Source: Kdnugget12942
Whether you are learning data science for the first time or refreshing your memory or catching up on latest trends, these free books will help you excel through self-study.
Source: Kdnugget30255
Top 10 data mining algorithms, selected by top researchers, are explained here, including what do they do, the intuition behind the algorithm, available implementations of the algorithms, why use them, and interesting applications.
Source: Hackerbits17649
Tech improvement all across the industries have helped to develop Artificial Intelligence for advancement of businesses today. And, Machine Learning(ML) is a branch of AI. So, if we basically talk about Machine Learning (ML),it actually provides computers with the ability to do certain tasks, such as recognition, diagnosis, planning, robot control, prediction, etc., without being explicitly programmed. It focuses on the development of algorithms that can teach themselves to grow and change when exposed to new data. The process of ML is somehow similar to that of Data Mining. Both search through data to look for patterns. But, ML uses the data to improve the program's own understanding. ML programs are used to detect patterns in data and adjust program actions accordingly.
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Taking decisions based on Data is not only an inherent sense but a strong commercial sense too.
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A Machine Learning Framework is an interface, library or tool which allows developers to more easily and quickly build machine learning models, without getting into the nitty-gritty of the underlying algorithms. It provides a clear, concise way for defining machine learning models using a collection of pre-built, optimized components.
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Growing amount of data available to the organization has led to the development of many analytical tools. As the big data has no significance to the company until and unless it can be converted into valuable insights.
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For beginners and students to have better understanding about the emerging technologies and charity about the artificial intelligence, one need to understand the basic terms, concepts related to it.
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Web scraping is also known as web harvesting or data extraction. It is used for extracting data from the website. Web scraping a web page included fetching and extracting. Fetching is something what we are downloading. So we can say that web crawling is a most important component of web scraping, to fetch pages for later processing. Once fetched, then the extraction takes place. It is also used for contact scrapping, and as a component of applications used for web indexing, web mining, and data mining.
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I was listening to an old episode of Partially Derivative, a podcast on data science and the news. One of the hosts mentioned that we're now living in the "golden age of data science instruction" and learning materials. I couldn't agree more with this statement. Each month, most publishers seem to have another book on the subject and people are writing exciting blog posts about what they're learning and doing.
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Nowadays, there is a huge list of powerful data visualization tools to help you illustrate your ideas, visualize your data, make it talk, share your significant analytics with customers and the global community.
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Here is a great collection of eBooks written on the topics of Data Science, Business Analytics, Data Mining, Big Data, Machine Learning, Algorithms, Data Science Tools, and Programming Languages for Data Science.
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Whether you are learning data science for the first time or refreshing your memory or catching up on the latest trends in Data Mining, Data Analysis, these free books will help you excel through self-study.
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More free resources and online books by leading authors about data mining, data science, machine learning, predictive analytics, and statistics.
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IBM recently predicted that in the next two years there might be a boost of 28 percent in the number of employed Data scientists.
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Machine Learning is the subset of Artificial Intelligence which allow systems to perform the specific tasks. Machine Learning and Data Mining work closely as both search through data to look for patterns basically it detects patterns in data and adjust program actions accordingly.
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Data mining specialists have careers dedicated for better understanding about how to process and draw conclusions from the large amounts of information.
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This list contains free learning resources for data science, machine learning and big data related concepts, techniques, and applications. Inspired by Free Programming Books.
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There are many different types of analysis to retrieve information from big data. Each type of analysis will have a different impact or result. The data mining technique you should use, depends on the kind of business problem that you are trying to solve.
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Data mining is sifting through all of the data collected by a business or organization, searching for relationships so that reasonable predictions can be made with regard to behavior. This kind of activity is most common among businesses that deal with consumer behavior of any kind.
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Data is absolutely priceless and the new gold for all businesses. But it is not a cake walk to analyze it as greater things come at a greater cost. With the tremendous growth in data, we need a process to extract useful insights from the raw data.
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Data mining techniques have advantages for several types of businesses, as well as there are more to be discovered over time. Since the era of the computer, things have been changing pretty quickly and every new step in the technology is equivalent to a revolution.
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Data mining is the process through which we analyze the behavior of the customer towards the contribution by the business. New and advanced technologies are also covered rather than the data. It helps you to extract and analyze meaning through expansive sets of data. This data is used in summarizing the valuable information which is to be used for increasing revenue, and also gather information on business or product. In this technological world, business organizations are benefited and they are able to make business decisions which are more definite, which help them to increase their sales and earn more profit. All the new products and services are introduced and all the marketing advertising, data mining improves customer obedience and find hidden profits of the business.
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Machine Learning is the subset of Artificial Intelligence and all are the part of computer science. It is a data analysis tool that helps us in automating the tasks. Alternatively, it also provides the machines (computer systems) with the capability to learn from the data, without external help to make decisions with minimum human interference. With the evolution of new technologies, machine learning has changed a lot over the past few years.
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The main motive of every business is to earn a profit and correct decisions help you to attain effectively. Every leader of the business takes a number of decisions which have a great impact on the work in multiple ways. Therefore, to become a profitable organization the ultimate goal should be an effective decision. Business intelligence helps in the plans which are implemented successfully which is the foremost need of every business. New strategies and procedure of right planning are implemented by business intelligence. Data is being analyzed, stored and accessed by the technologies of business intelligence.
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Data mining is the process of examining a data set to extract certain patterns. Companies use this process to determine the outcome of their existing goals. They summarize this information into useful methods to create revenue and/or cut costs. When search engines are accessed, they begin to build lists of links from the first page it accesses. It continues this process throughout the site until it reaches the root page.
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Now have you ever come across the term data mining? As the name implies, it is an analytic process used to explore a large amount of data in regards to consistent patterns and systematic relationships between variables. Businesses prefer data mining because it aims to predict. Predictive analyses, on the other hand, refine data resources, in particular, to extract hidden value from those newly discovered patterns. �¢??Data mining + Domain knowledge =>Predictive Analytics =>Business Value�¢??
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Data mining is the method of sorting through massive information sets to spot patterns and establish relationships to unravel issues through information analysis.
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All professionals I'm sure looking ahead to a new start and want to increase their data analysis skills. So here is the collection of books through which data scientist can sharpen up their knowledge and skills.
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Data scientists are increasingly important to organizations as decisions become more data-driven. You need to be able to tell the real and talented data scientists from a charlatan who talks the talk. Here are five questions every data scientist should be able to answer.
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What is Data Mining? Well, it can be defined as the process of getting hidden information from the piles of databases for analysis purposes. Data Mining is also known as Knowledge Discovery in Databases (KDD). It is nothing but the extraction of data from large databases for some specialized work.
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These are the top 10 machine learning which might lead you towards good skills and vast opportunities for your career. All these languages are the highly rated machine learning repositories.
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Global Data Mining Software Market report offers clients the most efficient and dependable insight into the Data Mining Software market, ranging across different major players.
Source: ReportsandReports4986
Positive returns on analytics investment require management action. But many managers are reluctant to take action based on analytics, especially when the numbers don't seem to match with their own gut understanding.
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Data science is giving too many opportunities today in the professional world. As the number of business concerns using data analytics is on the rise, so is the number of jobs in this field.
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If you're a beginner or experienced as a Data Scientist then you must aware of these data science books. Books are the best source to get insights and increase our knowledge.
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As you can see these days there are millions of data generated and big data has become the most demanding tech in the world.
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Data science, Data mining and Data analysis are abuzz today with the number of jobs growing rapidly with each coming day in these fields.
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A Business Intelligence technology is used by the organizations to analyze business information which includes past and present data and drawing insights from that data.
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Machine Learning is an application of Artificial Intelligence which provides machines with the capability to take decisions without any human intervention.
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The Graphics supported by R and its statistical features are considered better than SAS.
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LinkedIn is a very good place for the professionals to gather, connect with others, share ideas and network. If you are in a Data Science or predictive analytics space, or if you are seeking for additional insights and what all industries are talking about, for all these LinkedIn professional groups are a great place to start.
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Becoming a Data Scientist might be on your mind right now. Learn Data Science step by step through real Analytics examples.
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A recent report from Gartner predicts that 40% of Data Science tasks will become automated by 2020.
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The 7 most important terms in Data Science that every Data Scientist must know while making a career in Data Science are discussed in the present article.
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See the major difference between the sub-categories of data science, machine learning, and big data.
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Many technical skills require training and experience to master. They are also typically a type of hard skill. Hard skills are those that can be taught in a classroom and can be defined, evaluated, and measured.
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In this data-driven world usage of words like Data Analysis, Data Mining, Data Science, Machine Learning, and Big Data are common and are often used by the professionals in the field. Often these terms are confusing to a beginner and the terms seem similar to a novice in the field.
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So here are some Big Data Analytics tools which we will explore in detail in this article.
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If you really want to know the demand of data science, this article will give you a complete check of who is a data scientist and the future jobs of a data scientist with a pay scale in the near future.
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Often we commit the silly mistakes in Data Visualization which lead to wrong interpretation of the data, but with good practices and good techniques effective visualizations could be created in a lesser amount of time.
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To make any business successful and work for a longer time, a Proactive and forward-looking approach is needed and this is the only approach by which businesses plan strategies for the future. Using Predictive Analytics businesses make use of their past and present data to predict future certainties.
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In this article, we will look at the top 5 online courses for Machine Learning. These courses are designed in a way that every beginner and professional can be benefitted from the course.
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The real power of machine learning resides in its algorithms, which make even the most difficult things capable of being handled by machines.
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Some books which will help data scientist to build their career with these famous Data Science courses.
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Welcome to this free online class on machine learning. Machine learning is one of the most exciting recent technologies.
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Machine Learning is a branch of computer science, a field of Artificial Intelligence. It is a data analysis method that further helps in automating the analytical model building.
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Build a strong foundation for entering the world of Machine Learning and data science with the help of this comprehensive guide.
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Data Science Tools, Data Analysis, Data Warehousing, Data Mining, Microsoft Azure, MySQL, DataRobot, Amazon
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Machine learning is the science of getting computers to act without being explicitly programmed. In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome.
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A data scientist will be responsible for designing and implementing various processes and different layouts for the intricate and large-scale datasets that are basically used for modeling, data mining, and various research purposes.
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Over the last several years, the financial services industry has been focusing on how to use Artificial Intelligence (AI) to exceed customer expectations, reduce operational costs, and make smarter overall business decisions.
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Data science is a present-day technology world using a very common term. It is a multi-disciplinary entity that deals with data in a structured and unstructured manner.
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Since the importance of data analytics is burgeoning day by day, hence the companies are appointing the sagacious professionals who will provide the company with the wider insights of the structured data.
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Machine Learning can be an incredibly beneficial tool to uncover hidden insights and predict future trends.
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The wide application of Information Technology and Computer Science has given rise to so many new fields in the corporate sector which have enormous potentials and possibilities.
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Data science is the buzzword that has gripped the entire world. Despite its ever-growing popularity, there are many questions related to this field.
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Artificial intelligence (AI) is a field within computer science that is attempting to build enhanced intelligence into computer systems.
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Data science makes use of a scientific approach to gain insight and knowledge out of data. It employs different processes, systems, and algorithms to derive insights out of structured and structured data.
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You'll learn a range of techniques, starting with simple linear regression and progressing to deep neural networks.
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Machine Learning is a branch of computer science, a field of Artificial Intelligence. It is a data analysis method that further helps in automating the analytical model building.
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Machine learning tools are algorithmic applications of artificial intelligence that give systems the ability to learn and improve without ample human input; similar concepts are data mining and predictive modeling.
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Below is the list of top 10 of data analytics tools, both open-source and paid version, based on their popularity, learning and performance.
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Big Data Infrastructure Management in Cloud Data Centers has been one of the fruitful solutions suggested for countering rising infrastructural costs.
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Data science already has a market revenue of $2.71 billion and it is expected to touch $20 billion marks by 2025.
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Machine learning is the science of getting computers to act without being explicitly programmed. In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome.
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Today data science is being used by industries, so prolifically that the demand of data scientists has risen too.
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Having mass amounts of data means nothing; what you do with that data is what matters. That's where data mining comes in.
Source: HOB7725
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