Small businesses use AI Tools to increase their leads by 50%

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Artificial Intelligence (AI) tools and resources have become indispensable to today’s industry. The 2019 study by Gartner shows that in the last four years, the use of AI has increased by 270%. In the last year alone, the number of organizations that have deployed AI in some way has more than triples from 4% to 14%.

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Five predictions for the future of the modern Data Stack

The Modern Data Stack is quickly picking up steam in tech circles as the go-to cloud data architecture, and although its popularity has been quickly rising, it can be ambiguously defined at times. In this blog post, we’ll discuss what it is, how it came to be, and where we see it going in the future. Regardless of whether you’re new to the modern data stack or have been an early adopter, there should be something of interest for everyone.

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Market Research Report — Know the unbiased, accurate report of Market Research Here

AI market research

Market research report offer definite examinations about a particular market circumstance inside a geographic region. These reports contain data on market moves because of social, innovative, and monetary changes. Explaining market openings and how to reap these centers around the hierarchical arrangement, business cycles, and capital constructions.

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10 secret Tableau features you should start using right away

Tableau expert

The power of Tableau is its ease of use. With only a few clicks you can drag and drop different data fields to create your view. As per all the other tools, it takes time to explore and master all Tableau features but with this article, I aim to explain 10 tips and tricks which will help you to build compelling dashboards in a timely fashion.

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The dark side of Data Science

As I discuss in my article “Myths of Modelling: Data Speak”, Positivism — and, by association, its mythical beliefs — had been pretty thoroughly discredited by the 1960s. Unfortunately, as if often the case in the history of ideas, the counter-revolution over-compensated. Where the early revolutionaries would loosen the chains of narrow empiricism and open up for a more enlightened dialogue between hypotheses and the data that inspire and regulate them, the next generation would throw empiricism out all together. In the ensuing vacuity of common sense, practitioners had little choice but to crawl back to frameworks steeped in positivism.

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Multidimensional multi-sensor time-series data analysis framework

Multidimensional multi-sensor time-series data analysis framework. In this blog post, I will take you through my package “msda” useful for time-series sensor data analysis. A quick introduction about time-series data is also provided. The demo notebook can be found on here. One of the specific use case applications focused on “Unsupervised Feature Selection” using the package can be found in the blog post here.

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Retraining Machine Learning Model approaches

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Generally machine learning models will be trained by some learning between set of input features and dependent feature or target variable. The aim of the model is to minimize the prediction error by applying or optimizing cost functions, and when we found some optimized models, we will deploy into the production and the aim is that model will generate accurate predictions on future unseen data as well so the goal is that model will predict the future unseen data as accurately as data used during the training period.

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Introducing “Lux” for faster Data exploration

Most of the time spent by data scientists is in data cleaning , data exploration . A detail EDA (exploratory data analysis) is very much important and significant in the data science life cycle. In the year 2020 , there has been lot of automatic EDA libraries have been developed to save the time for the data scientist. Some of the most commonly used automatic EDA are listed in the following blog.

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How AI has enhanced Sentiment Analysis using Product Review data

Customer feedback is great. But have you been able to turn that feedback into meaningful customer insights? A few years back, brands depended on surveys to gauge customers’ feelings about how their products were performing.  From the product reviews, they were able to somehow get a grip on the general feeling of good, bad, or neutral response to their marketing campaign or product. There is, however, so much more information in the form of unstructured data that brands need to lay their hands on to better analyze the sentiments of their customers. 

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20 AutoML libraries for the Data Scientists

AutoML refers to automated machine learning. It explains how the end to end process of machine learning can be automated at the organizational and educational level. Initially all these steps were done manually. The demand for machine learning is increasing day by day. Let’s see some of the most common AutoML libraries which are present in different programming languages.

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Why building a Machine Learning Model is like cooking

The first step in building a machine learning model is to prepare the data. This may involve pulling raw data from a variety of sources to load into a database. Likewise, the first step in cooking is to get the ingredients (the data). You may need to go to the grocery store to buy ingredients you don’t have at home (pull from a variety of sources).

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Analyzing the chaotic Presidential Debate 2020 with text mining techniques

Thanks to the internet, now the world knew about the Presidential Debate 2020 that went out of control. All of the major news stations were reporting about how the participants were interrupting and sniping at one another.
I decided to put together an article that focuses on analyzing the words used in the event and see if there are any hidden insights.

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Adopt the Automation Route to scale up your business

Machine Learning is advancing steadily, enabling computers to understand natural language patterns and think somewhat like humans. The advances in Artificial Intelligence (AI) are increasing the prospects of businesses to automate tasks. With automation, you can save time and bring in more productivity for your business.

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