Data Science 101

DECEMBER 11, 2019

This weeks guest post comes from KDD (Knowledge Discovery and Data Mining). Every year they host an excellent and influential conference focusing on many areas of data science. Honestly, KDD has been promoting data science way before data science was even cool. 1989 to be exact. The details are below.

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KDD Knowledge Discovery Data mining Data Science 81

Smart Data Collective

SEPTEMBER 16, 2020

Predictive analytics, sometimes referred to as big data analytics, relies on aspects of data mining as well as algorithms to develop predictive models. These predictive models can be used by enterprise marketers to more effectively develop predictions of future user behaviors based on the sourced historical data.

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Predictive Analytics Analytics Predictive Modeling Data mining 139

CIO Business Intelligence

JUNE 7, 2022

Data analytics draws from a range of disciplines — including computer programming, mathematics, and statistics — to perform analysis on data in an effort to describe, predict, and improve performance. What are the four types of data analytics? Data analytics includes the tools and techniques used to perform data analysis.

Data Analytics 135

Data Analytics Diagnostic Analytics Management Analytics 135

Smart Data Collective

JUNE 4, 2021

Here are the chronological steps for the data science journey. First of all, it is important to understand what data science is and is not. Data science should not be used synonymously with data mining. Mathematics, statistics, and programming are pillars of data science. Deep Learning.

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Data Science Statistics Deep Learning Machine Learning 133

Domino Data Lab

MARCH 11, 2021

Here are several key considerations you should take into account when selecting a machine learning framework for your project. When you start your search for a machine learning framework, ask these three questions: Will you use the framework for deep learning or classic machine learning algorithms?

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Machine Learning Deep Learning Insurance Modeling 143

CIO Business Intelligence

FEBRUARY 10, 2023

Predictive analytics in business Predictive analytics draws its power from a wide range of methods and technologies, including big data, data mining, statistical modeling, machine learning, and assorted mathematical processes. from 2022 to 2028.

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Predictive Analytics Analytics Predictive Modeling Forecasting 145

Smart Data Collective

FEBRUARY 14, 2021

Do Your Research with Data Mining. Big data makes it a lot easier to research new opportunities. there are a lot of great big data repositories on customer desires and marketing trends. You need to use Hadoop tools to mine this data and find out more about your target customers and product requirements.

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Data-driven Big Data Deep Learning Data mining 108

Analytics Vidhya

DECEMBER 13, 2021

Pursuing any data science project will help you polish your resume. The post Top Data Science Projects to add to your Portfolio in 2021 appeared first on Analytics Vidhya. Introduction 2021 is a year that proved nothing is better than a Proof of Work to evaluate any candidate’s worth, initiative, and skill.

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Data Science Analytics Data mining Deep Learning 353

Sisense

APRIL 10, 2020

Some standard Python libraries are Pandas, Numpy, Scikit-Learn, SciPy, and Matplotlib. These libraries are used for data collection, analysis, data mining, visualizations, and ML modeling. Libraries used for NLP are: NLTK, gensim, SpaCy , glove, and Scikit-Learn. Every library has its own purpose and benefits.

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Deep Learning Data Science Machine Learning Visualization 98

Analytics Vidhya

OCTOBER 28, 2022

This article was published as a part of the Data Science Blogathon. Introduction The generalization of machine learning models is the ability of a model to classify or forecast new data. When we train a model on a dataset, and the model is provided with new data absent from the trained set, it may perform […].

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Machine Learning Modeling Forecasting Data Science 399

Rocket-Powered Data Science

DECEMBER 16, 2018

They are not machine learning algorithms in themselves, but GAs can be applied across ensembles of machine learning models and tasks, in order to find the optimal model (perhaps globally optimal model) across a collection of locally optimal solutions. Workshop on Meta-Learning (MetaLearn 2018).

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Machine Learning Metrics Optimization Data Science 203

Smart Data Collective

AUGUST 20, 2021

Here are several steps to do before you find an ideal monetization way through the use of machine learning algorithms: 1. Machine learning and data mining tools can be very useful in this regard. Machine learning can be useful for solving monetization challenges.

Machine Learning 90

Machine Learning Data mining Advertising Deep Learning 90

CIO Business Intelligence

AUGUST 11, 2023

Lilly Translate uses NLP and deep learning language models trained with life sciences and Lilly content to provide real-time translation of Word, Excel, PowerPoint, and text for users and systems. Licensed by MIT, SpaCy was made with high-level data science in mind and allows deep data mining.

Unstructured Data 142

Unstructured Data Machine Learning Data Science Data mining 142

Rocket-Powered Data Science

DECEMBER 15, 2018

In deep learning, as in typical neural network models, the method by which those adjustments to the model parameters are estimated ( i.e., for each of the edge weights between the network nodes) is called backpropagation.

Machine Learning 171

Machine Learning Optimization Metrics Modeling 171

Smart Data Collective

APRIL 3, 2020

How Data-Driven Bots Can Help You. A couple of months ago, Hacker Moon wrote a great article on the use of deep learning to create chatbot s. This is one of the most important benefits of big data. Fortunately, big data is simplifying the research process as well. Chatbots for Giveaways.

Big Data 118

Big Data Data-driven Data mining Software 118

Smart Data Collective

MAY 8, 2022

Above all, there needs to be a set methodology for data mining, collection, and structure within the organization before data is run through a deep learning algorithm or machine learning. By doing this, businesses can form their finance & marketing strategies with the new information they have gathered.

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Big Data Data Analytics Analytics Cost-Benefit 122

CIO Business Intelligence

JANUARY 19, 2024

The exam tests your knowledge of and ability to integrate machine learning into various tools and applications. To pass the exam, you need to be experienced with the foundational principles of ML and deep learning, building ML models, image recognition algorithms, deep neural networks, and natural language processing.

Data Science 127

Data Science Machine Learning Predictive Modeling Forecasting 127

CIO Business Intelligence

APRIL 6, 2022

For example, Dell Technologies Validated Designs for Splunk power AIOps by gathering real-time data, mining it for insights, and then delivering these insights to management. Modern data analytics spans a range of technologies, from dedicated analytics platforms and databases to deep learning and artificial intelligence (AI).

Data mining 73

Data mining Deep Learning Insurance Visualization 73

FineReport

DECEMBER 19, 2019

Professional data analysts must have a wealth of business knowledge in order to know from the data what has happened and what is about to happen. In addition, tools for data analysis and data mining are also important. Excel, Python, Power BI, Tableau, FineReport are frequently used by data analysts.

Knowledge Discovery 98

Knowledge Discovery Visualization Data mining Reporting 98

CIO Business Intelligence

MARCH 13, 2024

L’analisi dei dati attraverso l’apprendimento automatico (machine learning, deep learning, reti neurali) è la tecnologia maggiormente utilizzata dalle grandi imprese che utilizzano l’IA (51,9%). Le reti neurali sono il modello di machine learning più utilizzato oggi.

Machine Learning 106

Machine Learning Deep Learning Big Data Testing 106

Smart Data Collective

APRIL 3, 2020

How Data-Driven Bots Can Help You. A couple of months ago, Hacker Moon wrote a great article on the use of deep learning to create chatbot s. This is one of the most important benefits of big data. Fortunately, big data is simplifying the research process as well. Chatbots for Giveaways.

Big Data 84

Big Data Data-driven Data mining Software 84

IBM Big Data Hub

JULY 6, 2023

The fields have evolved such that to work as a data analyst who views, manages and accesses data, you need to know Structured Query Language (SQL) as well as math, statistics, data visualization (to present the results to stakeholders) and data mining. Machine learning and deep learning are both subsets of AI.

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Machine Learning Data Science Statistics Deep Learning 54

Jedox

JULY 31, 2018

It quickly processes large amounts of data from internal and external sources, so users can recognize patterns and gain deeper insights to make better decisions. It runs statistics and algorithms (also known as data mining) on masses of historical data to calculate probabilities and future events.

Technology 44

Technology Prescriptive Analytics Machine Learning Business Intelligence 44

IBM Big Data Hub

AUGUST 28, 2023

One of the best ways to take advantage of social media data is to implement text-mining programs that streamline the process. What is text mining? And with advanced software like IBM Watson Assistant , social media data is more powerful than ever.

Data mining 53

Data mining Machine Learning Deep Learning Marketing 53

IBM Big Data Hub

AUGUST 11, 2023

Machine learning (ML), a subset of artificial intelligence (AI), is an important piece of data-driven innovation. Machine learning engineers take massive datasets and use statistical methods to create algorithms that are trained to find patterns and uncover key insights in data mining projects.

Data Science 53

Data Science Machine Learning Cost-Benefit Deep Learning 53

BizAcuity

MARCH 31, 2022

AI can be applies to all 3 major types of analytics: Descriptive Analytics: The entire journey of the descriptive and diagnostic analytics process includes data extraction, data aggregation and data mining; 3 applications where AI is widely used to reduce costs, and eliminate complex actions.

Data Analytics 52

Data Analytics Analytics Prescriptive Analytics Predictive Analytics 52

Domino Data Lab

AUGUST 1, 2021

The interest in interpretation of machine learning has been rapidly accelerating in the last decade. This can be attributed to the popularity that machine learning algorithms, and more specifically deep learning, has been gaining in various domains. Methods for explaining Deep Learning. Guestrin, C.,

Modeling 139

Modeling Deep Learning Machine Learning Knowledge Discovery 139

IBM Big Data Hub

DECEMBER 15, 2023

PyTorch is an open-source AI framework offering an intuitive interface that enables easier debugging and a more flexible approach to building deep learning models. It is a popular choice among researchers and developers for rapid software development prototyping and AI and deep learning research. Morgan and Spotify.

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Deep Learning Experimentation Machine Learning Risk 64

Ontotext

MAY 22, 2023

Luckily, the text analysis that Ontotext does is focused on tasks that require complex domain knowledge and linking of documents to reference data or master data. We use other deep learning techniques for such tasks. Delivering better data mining, NLP and pattern identification – you can make better decisions.

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Management Unstructured Data Metadata Cost-Benefit 59