Fri.Oct 28, 2022

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Non-Generalization and Generalization of Machine learning Models

Analytics Vidhya

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 […]. The post Non-Generalization and Generalization of Machine learning Models appeared first on Analytics Vidhya.

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What transformational leaders too often overlook

CIO Business Intelligence

High-performing CIOs know that digital mastery depends on a strong foundation of rock-solid infrastructure, information security, enterprise data management, and sound IT governance. But for all the emphasis on cutting-edge technology for business transformation, IT infrastructure too often gets short shrift. Infrastructure, what happens behind the IT screen, and related support activities remains poorly understood, underappreciated, and mismanaged in 89% of enterprises today, according to a rec

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MLOps In Educational Data Mining

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Similar to other fields like healthcare, education is an area that is being penetrated by technology and data science. Many fields have evolved, such as Educational Data Mining EDM, which is a field dedicated to finding actionable insights from educational settings. It […].

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How to Make Python Code Run Incredibly Fast

KDnuggets

In this article, I have explained some tips and tricks to optimize and speed up Python code.

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Peak Performance: Continuous Testing & Evaluation of LLM-Based Applications

Speaker: Aarushi Kansal, AI Leader & Author and Tony Karrer, Founder & CTO at Aggregage

Software leaders who are building applications based on Large Language Models (LLMs) often find it a challenge to achieve reliability. It’s no surprise given the non-deterministic nature of LLMs. To effectively create reliable LLM-based (often with RAG) applications, extensive testing and evaluation processes are crucial. This often ends up involving meticulous adjustments to prompts.

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Data Lake or Data Warehouse- Which is Better?

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Data is defined as information that has been organized in a meaningful way. We can use it to represent facts, figures, and other information that we can use to make decisions. Data collection is critical for businesses to make informed decisions, understand customers’ […].

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The Current State of Data Science Careers

KDnuggets

If you’re someone in data science or aiming to get into a data science career, this article will give you a comprehensive analysis of the state of the field.

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Macroeconomic jitters further slow AWS growth in Q3

CIO Business Intelligence

Macroeconomic conditions led by the pandemic and the geopolitical crisis in Ukraine have further slowed down growth of Amazon’s cloud computing unit, Amazon Web Services (AWS), in the third quarter of 2022. Amazon on Thursday said AWS had raked in revenue of $20.5 billion for the quarter ended September 30, up 27.5% year-on-year. However, revenue for AWS grew at 33% year-on-year at 19.74 billion in the previous quarter (ended June 30).

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Handling Missing Data with SimpleImputer

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Missing data in machine learning is a type of data that contains “None” or “NaN” type of values. One should take care of the missing data while dealing with machine learning algorithms and training. Missing data can be filled using basic python […].

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Don’t Become a Commoditized Data Scientist

KDnuggets

Unicorns don't exist. Aim instead to be an endangered species.

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The Double-Edged Sword of Model Optimization

Dataiku

This is a guest article from Juan Navas. Navas has a Bachelor's in computer science and a Master's in big data. He worked for several years in the telecom sector on cloud computing, 5G, and micro-service architectures based on Docker containers. He works on blockchain DApps, mainly in Ethereum blockchain, programming smart contracts and leading an ICO for a startup.

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Driving Business Impact for PMs

Speaker: Jon Harmer, Product Manager for Google Cloud

Move from feature factory to customer outcomes and drive impact in your business! This session will provide you with a comprehensive set of tools to help you develop impactful products by shifting from output-based thinking to outcome-based thinking. You will deepen your understanding of your customers and their needs as well as identifying and de-risking the different kinds of hypotheses built into your roadmap.

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3 Reasons for Software Companies to Add Embedded BI!

Smarten

3 Benefits of Embedded BI for OEM and ISV Partners! If yours is a software business and you are looking for ways to improve the value of your products to your customers and clients; if you want to earn more revenue, expand your market visibility and ensure growth…without expensive investment and time-consuming development projects, there is a way to achieve your goals!

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Big, bigger, giant. The rise of giant AI models

CONTACT Software

The evolution of language models in the field of NLP (Natural Language Processing) has led to huge leaps in the accuracy of these models for specific tasks, especially since 2019, but also in the number and scope of the capabilities themselves. As an example, the GPT-2 and GPT-3 language models released with much media hype … Continue reading "Big, bigger, giant.

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Autonomous and As-A-Service Models Will Rely on Predictive Maintenance

Teradata

Data will drive the business models of next generation commercial vehicle suppliers. Find out how.

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Generative Pre-training (GPT) for Natural Language Understanding

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Source: Canva Introduction In 2018 the researchers of OpenAI presented a framework for achieving strong natural language understanding (NLU) with a single task-agnostic model through generative pre-training and discriminative fine-tuning. In this article, we will look at this groundbreaking work in more detail, which […].

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How to Build an Experimentation Culture for Data-Driven Product Development

Speaker: Margaret-Ann Seger, Head of Product, Statsig

Experimentation is often seen as an aspirational practice, especially at smaller, fast-moving companies who are strapped for time and resources. So, how can you get your team making decisions in a more data-driven way while continuing to remain lean and maintaining ship velocity? In this webinar, Margaret-Ann Seger, Head of Product at Statsig, will teach you how to build an experimentation culture from the ground-up, graduating from just getting started with data-driven development to operating

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How To Cultivate Data-Driven Decision-Making In Your Workplace

Smart Data Collective

The benefits of investing in big data cannot possibly be understated. A report by McKinsey showed that data-driven companies have 15-25% higher earnings before interest, taxes, depreciation and amortization. Most of the discussions on the benefits of using data have centered around larger companies, but smaller firms should take advantage of big data as well.

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The DataHour Synopsis: Hands-on with A/B Testing

Analytics Vidhya

Overview Analytics Vidhya has long been at the forefront of imparting data science knowledge to its community. With the intent to make learning data science more engaging to the community, we began with our new initiative- “DataHour”. DataHour is a series of webinars by top industry experts where they teach and democratize data science knowledge. […].

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