Fri.Aug 12, 2022

article thumbnail

Outliers Pruning Using Python

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction When it comes to data cleaning, it is not always that we have to deal with NaN or Zero values so that we can remove them, and data cleaning is done! In real-time practical projects, things aren’t that simple. We have to […]. The post Outliers Pruning Using Python appeared first on Analytics Vidhya.

article thumbnail

Data Transformation: Standardization vs Normalization

KDnuggets

Increasing accuracy in your models is often obtained through the first steps of data transformations. This guide explains the difference between the key feature scaling methods of standardization and normalization, and demonstrates when and how to apply each approach.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

A Comparative Analysis of Community Detection Algorithms

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Community detection in a network identifies and groups the more densely interconnected nodes in a given graph. This graph can take the form of a social network graph, a biological network, or a representation of a local network of computers, for example. Clusters of […].

article thumbnail

The Importance of Experiment Design in Data Science

KDnuggets

Do you feel overwhelmed by the sheer number of ideas that you could try while building a machine learning pipeline? You can not take the liberty of trying all possible ways to arrive at a solution - hence we discuss the importance of experiment design in data science projects.

article thumbnail

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.

article thumbnail

#ClouderaLife Spotlight: Preety Vatvani

Cloudera

Preety Vatvani, working out of Cloudera’s Singapore office, is Cloudera’s first lead development team lead. Her role is to recruit and work with a team of interns interested in a career in technology sales, and train them so they can field inside sales opportunities and gain valuable early career experience. In this #ClouderaLife Spotlight we talked to Preety about how she got this program off the ground.

Sales 83
article thumbnail

How to Perform Motion Detection Using Python

KDnuggets

In this article, we will specifically take a look at motion detection using a webcam of a laptop or computer and will create a code script to work on our computer and see its real-time example.

IT 103

More Trending

article thumbnail

A Lifecycle Approach for Responsible AI

Dataiku

Managing AI-related risk is commonly cited as a top AI adoption challenge by organizations across a wide variety of industries that are trying to achieve Responsible AI. Responsible AI is no longer just a “nice to have” but a key driver of AI adoption.

Risk 64
article thumbnail

Best Used Servers for Databases and Cloud Computing

Smart Data Collective

Cloud technology is becoming more important than ever. Precedence Research projects that global companies will spend over $1.6 trillion on cloud services in 2030. Companies will need to get used to investing in the right infrastructure to make the most of their cloud capabilities. This is going to require them to invest in the best servers to connect with cloud services, especially if they want to host their own.

article thumbnail

Thermo Fisher transforms its customer experience

CIO Business Intelligence

With its business rapidly growing and customer expectations rising, Thermo Fisher Scientific is turning to machine learning and robotic process automation (RPA) to transform the customer experience. Formed from the merger of Thermo Electron and Fisher Scientific in 2006, Thermo Fisher Scientific is one of the world’s largest suppliers of scientific instruments, reagents, and services, with more than 130,000 employees worldwide.

IT 104
article thumbnail

Struggling to Scale: How Finance Can Do More with Less

Jet Global

As the strategic role of finance teams continues to evolve, the Office of the CFO faces many new responsibilities. Resource allocation, however, does not always grow in tandem with those responsibilities, leading to scalability challenges for finance teams tasked with doing more with fewer resources. insightsoftware recently partnered with Hanover Research to find out how finance teams are meeting their expanded responsibilities and where they are encountering constraints that hamper their abili

Finance 52
article thumbnail

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.