Analytics Vidhya

MARCH 30, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon. The post Interpretation of Performance Measures to Evaluate Models appeared first on Analytics Vidhya. Introduction In the last year of my bachelor’s degree, I.

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Analytics Vidhya

JUNE 26, 2023

Introduction “Data Science” and “Machine Learning” are prominent technological topics in the 25th century. They are utilized by various entities, ranging from novice computer science students to major organizations like Netflix and Amazon. appeared first on Analytics Vidhya.

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Analytics Vidhya

AUGUST 28, 2021

This article was published as a part of the Data Science Blogathon “IF YOU ARE NOT TAKING CARE OF YOUR CUSTOMERS, YOUR COMPETITOR WILL” – Bob Hooey Overview: Customer Lifetime Value is the profit that a business will make from a specific customer over the period of their association with the business.

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Analytics Vidhya

JULY 8, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon Statistics. The post The Measure of Central Tendencies in Statistics -A Beginner’s Guide appeared first on Analytics Vidhya. Whenever I hear this term, I imagine of below Image.

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Analytics Vidhya

MARCH 23, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon. The post A/B Testing Measurement Frameworks ?- ?Every Every Data Scientist Should Know appeared first on Analytics Vidhya. What is A/B testing? A/B Testing(split testing) is basically the.

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Testing Measurement Data Science Publishing 258

Analytics Vidhya

DECEMBER 2, 2020

This article was published as a part of the Data Science Blogathon. Introduction One of the most used matrices for measuring model performance is. The post A Measure of Bias and Variance – An Experiment appeared first on Analytics Vidhya.

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KDnuggets

MAY 23, 2023

Data science, machine learning, and AI — all elements that could improve policing and community trust. Is your solution a winner?

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Analytics Vidhya

MARCH 10, 2022

This article was published as a part of the Data Science Blogathon. Photo by Ivan Bandura on Unsplash Introduction on Measurements Accuracy You’ve undoubtedly heard about gold diggers as well. The post When the Measurement’s Accuracy Misleads you! Your friend has a gold detector. […].

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Analytics Vidhya

FEBRUARY 11, 2023

Introduction The post-pandemic era has reinstated the importance of having more than one source of income as the cost of living has skyrocketed beyond measures. As a profession, data science is booming. Having side hustles in 2023 is great if you believe your knowledge and talents may help you earn more.

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Analytics Vidhya

SEPTEMBER 30, 2022

This article was published as a part of the Data Science Blogathon. Introduction Evaluation metrics are used to measure the quality of the model. Selecting an appropriate evaluation metric is important because it can impact your selection of a model or decide whether to put your model into production.

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CIO Business Intelligence

MAY 5, 2022

The boom in data science continues unabated. The work of gathering and analyzing data was once just for a few scientists back in the lab. Now every enterprise wants to use the power of data science to streamline their organizations and make customers happy. Data scientists use them to swap ideas and deliver ideas.

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Analytics Vidhya

AUGUST 5, 2022

This article was published as a part of the Data Science Blogathon. Measuring the strength of that relationship […]. Introduction One of the most important applications of Statistics is looking into how two or more variables relate.

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Smart Data Collective

JUNE 4, 2021

What is data science? Data science is analyzing and predicting data, It is an emerging field. Some of the applications of data science are driverless cars, gaming AI, movie recommendations, and shopping recommendations. These data models predict outcomes of new data. Where to start?

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Dataiku

NOVEMBER 6, 2020

When it comes to calculating the return on investment (ROI) of data science, machine learning, and AI projects, there’s a lot to unpack. Before even jumping into the measurements and calculations, it’s important to understand the scope. Are you measuring ROI gained from a data platform or a series of data initiatives themselves?

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Anmut

MARCH 22, 2023

This ultimately allows for more effective goal-setting, with targets determined according to both your data maturity right now and the desired stage you want to attain in the future. Why do we need data maturity models? A data maturity model helps your company measure its data and business health.

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Analytics Vidhya

APRIL 22, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon. Introduction What is the first measure coming into your mind. The post Confusion Matrix: Detailed intuition and trick to learn appeared first on Analytics Vidhya.

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Smart Data Collective

AUGUST 27, 2019

Well, your business is not immune to these attacks, and you should never be complacent with your existing security measures. Some of the people that will give high-level ideas on your security systems include data scientists, ethical hackers, and IT professionals. What Is Data Science? Associate Rule Learning (ARL).

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Analytics Vidhya

OCTOBER 5, 2020

This article was published as a part of the Data Science Blogathon. Quoting Peter Drucker, “What gets measured, gets managed.” Have you ever pondered. The post Power of Marketing and Business Analytics – An Approach to Grow your Business Online from Scratch appeared first on Analytics Vidhya.

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Business Analytics Marketing Analytics Measurement 339

IBM Big Data Hub

AUGUST 11, 2023

Because ML is becoming more integrated into daily business operations, data science teams are looking for faster, more efficient ways to manage ML initiatives, increase model accuracy and gain deeper insights. MLOps is the next evolution of data analysis and deep learning. Looking to scale the impact of AI across your business?

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Data Science Machine Learning Cost-Benefit Deep Learning 57

Analytics Vidhya

NOVEMBER 3, 2021

This article was published as a part of the Data Science Blogathon. Overview In NLP, tf-idf is an important measure and is used by algorithms like cosine similarity to find documents that are similar to a given search query. The post How sklearn’s Tfidfvectorizer Calculates tf-idf Values appeared first on Analytics Vidhya.

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Measurement Data Science Publishing Analytics 282

Analytics Vidhya

MAY 3, 2022

This article was published as a part of the Data Science Blogathon. Introduction on Time-Series A Time-Series is a sequence of data points collected at different timestamps. These are essentially successive measurements collected from the same data source at the same time interval.

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Analytics Vidhya

OCTOBER 5, 2021

This article was published as a part of the Data Science Blogathon Overview of SQL Query Optimization SQL Query optimization is defined as the iterative process of enhancing the performance of a query in terms of execution time, the number of disk accesses, and many more cost measuring criteria.

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Optimization Measurement Data Science Publishing 260

Data Science and Beyond

JANUARY 11, 2020

Back then, it seemed like “real” data science consisted of building and tuning machine learning models – that’s what Kaggle was all about. In reality, problem definition and solution measurement are more challenging and important. These solutions are software commodities.

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DataRobot Blog

JULY 28, 2022

This article presents a case study of how DataRobot was able to achieve high accuracy and low cost by actually using techniques learned through Data Science Competitions in the process of solving a DataRobot customer’s problem. Sensor Data Analysis Examples. The Best Way to Achieve Both Accuracy and Cost Control.

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Data Science and Beyond

NOVEMBER 22, 2015

Contrary to common belief, the hardest part of data science isn’t building an accurate model or obtaining good, clean data. It is much harder to define feasible problems and come up with reasonable ways of measuring solutions. This post discusses some examples of these issues and how they can be addressed.

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Analytics Vidhya

JANUARY 24, 2024

In this exploration, we simplify the complexities to understand the essence of vector norms—basic yet effective tools for measuring, comparing, and manipulating data with precision. Introduction Welcome to the practical side of machine learning, where the concept of vector norms quietly guides algorithms and shapes predictions.

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Machine Learning Measurement Analytics Deep Learning 274

Analytics Vidhya

MAY 2, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon. “Skewness essentially measures the symmetry of the distribution, while kurtosis. The post Shape of data: Skewness and Kurtosis appeared first on Analytics Vidhya.

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Analytics Vidhya

JANUARY 15, 2024

In a startling revelation, researchers at Anthropic have uncovered a disconcerting aspect of Large Language Models (LLMs) – their capacity to behave deceptively in specific situations, eluding conventional safety measures.

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Smart Data Collective

AUGUST 21, 2019

They recognize that the overemphasis on big data has created problems, so they have presented alternatives. Data Science Companies Focus on Optimal Data Utilization Rather than Just Emphasizing Data Scalability. Endor is a leading pioneer in data science. appeared first on SmartData Collective.

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Data Science Big Data Data Strategy Risk 68

bridgei2i

AUGUST 24, 2021

The Top Data Science Providers in India 2021: Penetration and Maturity (PeMa) Quadrant is an annual benchmarking study to classify vendors based on their analytics capability and maturity. More experienced and mature data science vendors are placed ahead of the curve in terms of industries and geographies served.

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bridgei2i

FEBRUARY 22, 2021

The benchmarking study known as AIM’s Penetration & Maturity Quadrant (PeMa matrix) is a vendor benchmark report which analyses leading Data Science Service Providers in India. Awards & Recognition News & Updates. www.BRIDGEi2i.com. BRIDGEi2i Analytics Solutions Contact. Venkat Subramanian.

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Data Science Contextual Data Consulting Digital Transformation 52

Jen Stirrup

MAY 5, 2020

Recently, I gave a Make Your Data Work Monday webinar on the complexities of the data sources for data science in Azure, and I thought it important enough to turn into an actual post. How can you differentiate the different opportunities to store your data in Azure?

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Machine Learning Data Science Data Lake Big Data 89

O'Reilly on Data

JANUARY 29, 2019

A recent survey investigated how companies are approaching their AI and ML practices, and measured the sophistication of their efforts. On the other hand, we wanted to measure the sophistication of their use of these components. Data scientists and data engineers are in demand.

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bridgei2i

JANUARY 25, 2022

The Basic Guide to Data Science at the Workplace. The Basic Guide to Data Science at the Workplace. In this podcast episode, AI enthusiasts Anirudh and Janci talk about how sincere curiosity and passion for learning can help anyone understand data science and become an active contributor. Subscribe Now.

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Data Science Machine Learning Data-driven Statistics 52

CIO Business Intelligence

JUNE 14, 2023

Getting the technology right can be challenging but building the right team with the right skills to undertake data initiatives can be even harder — a challenge reflected in the rising demand for big data and analytics skills and certifications. The number of data analytics certs is expanding rapidly.

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DataKitchen

FEBRUARY 1, 2021

DataOps addresses a broad set of use cases because it applies workflow process automation to the end-to-end data-analytics lifecycle. Each of these improvements can be measured and iterated upon. . The data team takes too long to deliver analytics. Users mistrust the data itself or the team working on the data.

Business Objectives 245

Business Objectives Cost-Benefit Measurement Metrics 245

KDnuggets

MARCH 11, 2020

Also: Recreating Fingerprints using Convolutional Autoencoders; A simple and interpretable performance measure for a binary classifier; Resources for Women in AI, Data Science, and Machine Learning; Trends in Machine Learning in 2020; A Crash Course in Game Theory for Machine Learning; and much more.

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