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Data science is an emerging, multidisciplinary field of scientific methods, processes, algorithm development and technology to extract knowledge or insights in ingenious ways from structured or unstructured data.
At the heart of data science is data. Buckets loads of it, streaming in and stored in enterprise data warehouses. According to IBM, globally, we currently generate over 2.5 quintillion bytes of data every single day.
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Python has a fantastic range of packages to produce mesmerizing visualizations. Here’s the finest free and open source Python visualization tools.
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Deep Learning is a subset of Machine Learning that uses multi-layers artificial neural networks to deliver state-of-the-art accuracy in tasks such as object detection, speech recognition, language translation and others. Think of Machine Learning as cutting-edge, and Deep Learning as the cutting-edge of the cutting-edge.
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This article recommends 33 free books which will teach you the basics of R, how to produce amazing plots, how to apply R to lots of disciplines, and how to efficiently program in R. Many of the books are open source.
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This is a short introductory training session on the use of Python in data science using Jupyter, pandas library and plotnine package. We focus on a common task in data science: import a data set, manipulate its structure, and then visualise the data. We shall use Python and a Jupyter Notebook to accomplish this task.
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This is a short introductory training session on the use of R in data science.
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Natural language processing (NLP) is a field of computer science, artificial intelligence, and computational linguistics concerned with the interactions between computers and human (natural) languages. It includes word and sentence tokenization, text classification and sentiment analysis, spelling correction, information extraction, parsing, meaning extraction, and question answering.
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Natural language processing (NLP) is an exciting field of computer science, artificial intelligence, and computational linguistics concerned with the interactions between computers and human (natural) languages. It includes word and sentence tokenization, text classification and sentiment analysis, spelling correction, information extraction, parsing, meaning extraction, and question answering.
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Natural language processing (NLP) is an exciting field of computer science, artificial intelligence, and computational linguistics concerned with the interactions between computers and human (natural) languages. It includes word and sentence tokenization, text classification and sentiment analysis, spelling correction, information extraction, parsing, meaning extraction, and question answering.
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