Sat.Nov 13, 2021 - Fri.Nov 19, 2021

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Talend Data Fabric Simplifies Data Life Cycle Management

David Menninger's Analyst Perspectives

Talend is a data integration and management software company that offers applications for cloud computing, big data integration, application integration, data quality and master data management. The platform enables personnel to work with relational databases, Apache Hadoop, Spark and NoSQL databases for cloud or on-premises jobs. Talend data integration software offers an open and scalable architecture and can be integrated with multiple data warehouses, systems and applications to provide a un

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The Fundamentals of Exploratory Data Analysis

Analytics Vidhya

This article was published as a part of the Data Science Blogathon Table of Contents Introduction About the Dataset Let’s Go 2D Scatter Plot 3D Scatter Plot Pair Plot Histogram Univariate Analysis using PDF CDF Mean, Variance, and Standard Deviation Median, Percentile, Quantile, IQR, MAD Box Plot Violin Plot Multivariate Probability Density Contour Plot Final Note […].

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Solve the Analytics Last-Mile Problem with a DataOps Process Hub

DataKitchen

Learn how a DataOps Process Hub enables Business Analysts to rapidly answer stakeholders' analytic questions without waiting on the centralized IT Team. The post Solve the Analytics Last-Mile Problem with a DataOps Process Hub first appeared on DataKitchen.

Analytics 130
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3 Differences Between Coding in Data Science and Machine Learning

KDnuggets

The terms ‘data science’ and ‘machine learning’ are often used interchangeably. But while they are related, there are some glaring differences, so let’s take a look at the differences between the two disciplines, specifically as it relates to programming.

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From Developer Experience to Product Experience: How a Shared Focus Fuels Product Success

Speaker: Anne Steiner and David Laribee

As a concept, Developer Experience (DX) has gained significant attention in the tech industry. It emphasizes engineers’ efficiency and satisfaction during the product development process. As product managers, we need to understand how a good DX can contribute not only to the well-being of our development teams but also to the broader objectives of product success and customer satisfaction.

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Why Is Data Consulting Essential For A New Business?

Smart Data Collective

More companies than ever are being driven by data. They use a number of important data analytics tools to help implement their functions more efficiently. Unfortunately, big data can be mysterious for many companies. Only 13% of companies with data strategies are meeting the objectives outlined in them. They need to know how to use it effectively to get the most value out of it.

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Build Face Recognition Attendance System using Python

Analytics Vidhya

This article was published as a part of the Data Science Blogathon Introduction In this article, you will learn how to build a face-recognition system using Python. Face recognition is a step further to face detection. In face detection, we only detect the location of the human face in an image but in face recognition, we […]. The post Build Face Recognition Attendance System using Python appeared first on Analytics Vidhya.

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Where NLP is heading

KDnuggets

Natural language processing research and applications are moving forward rapidly. Several trends have emerged on this progress, and point to a future of more exciting possibilities and interesting opportunities in the field.

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Use a Data Strategy to Make Your Startup Profitable

Smart Data Collective

Big data is no longer a luxury for businesses. It is a vital to any company that wants to succeed in all but the least competitive markets. In the information, there are companies with big data strategies and those that fall behind. Big data and business intelligence are essential. However, the success of a big data strategy relies on its implementation.

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How to Deploy Machine Learning(ML) Model on Android

Analytics Vidhya

This article was published as a part of the Data Science Blogathon Solving Machine learning Problems in a local system is only not the case but making it able to community to use is important otherwise the model is up to you only. When it is able to serve then you came to know the feedback and […]. The post How to Deploy Machine Learning(ML) Model on Android appeared first on Analytics Vidhya.

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3 Trends in Financial Services and AI for 2022

Dataiku

Many of you reading this will either have first-hand experience with the challenges of achieving data-driven success within financial firms or will have a reasonable concern that such success will not come easily to your organization. It is certainly true that finding actionable insights within your organizations — and then actually taking meaningful action based on those insights — is not a trivial matter.

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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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10 AI Project Ideas in Computer Vision

KDnuggets

The field of computer vision has seen the development of very powerful applications leveraging machine learning. These projects will introduce you to these techniques and guide you to more advanced practice to gain a deeper appreciation for the sophistication now available.

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Spotify Musicians Turn to Data Analytics to Boost their Careers

Smart Data Collective

Data analytics is becoming a crucial element of many business strategies. They have found that data analytics is a valuable component of marketing campaigns , financial planning objectives, human resource guidelines and much more. We have talked extensively about the types of industries that have been positively impacted by data analytics. Insurance, investing, logistics and digital marketing are among some of the professions most affected by big data.

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Here’s How to use Sankey Diagrams for Data Visualization

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction to Sankey Diagram for Data Visualization Very often, we are in a situation where we would have to visualize how data flows between entities. For example, let’s take the case of how residents have migrated from one country to another within the […]. The post Here’s How to use Sankey Diagrams for Data Visualization appeared first on Analytics Vidhya.

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NiFi as a Function in DataFlow Service

Cloudera

Introduction. With the general availability of Cloudera DataFlow for the Public Cloud (CDF-PC) , our customers can now self-serve deployments of Apache NiFi data flows on Kubernetes clusters in a cost effective way providing auto scaling, resource isolation and monitoring with KPI-based alerting. You can find more information in this release announcement blog post and in this technical deep dive blog post.

KPI 113
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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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Inside recommendations: how a recommender system recommends

KDnuggets

We describe types of recommender systems, more specifically, algorithms and methods for content-based systems, collaborative filtering, and hybrid systems.

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5 Applications for Corporate Text Analytics

Smart Data Collective

Text mining and text analysis are relatively recent additions to the data science world, but they already have an incredible impact on the corporate world. As businesses collect increasing amounts of often unstructured data, these techniques enable them to efficiently turn the information they store into relevant, actionable resources. Text analysis can fulfill multiple roles in the business world.

Analytics 116
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A Quick Tutorial on Clustering for Data Science Professionals

Analytics Vidhya

This is article was published as a part of the Data Science Blogathon. Welcome to this wide-ranging article on clustering in data science! There’s a lot to unpack so let’s dive straight in. In this article, we will be discussing what is clustering, why is clustering required, various applications of clustering, a brief about the […].

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Thinking of Analytics as a Product

Dataiku

14 years ago I (Doug) met with the director of business intelligence at NCR in his old headquarters in Dayton, Ohio. He’d recently finished a BusinessObjects implementation and proudly told me that he had 400 reports in production. I really didn’t have an understanding of that so I asked, “Is that too many or not enough?” It was obvious that he’d never considered the question, as a look of shock came over his face.

Analytics 111
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Entity Resolution Checklist: What to Consider When Evaluating Options

Are you trying to decide which entity resolution capabilities you need? It can be confusing to determine which features are most important for your project. And sometimes key features are overlooked. Get the Entity Resolution Evaluation Checklist to make sure you’ve thought of everything to make your project a success! The list was created by Senzing’s team of leading entity resolution experts, based on their real-world experience.

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Stop Blaming Humans for Bias in AI

KDnuggets

Can artificial intelligence be rid of bias? This is an important question, and it’s equally important that we look in the right place for the answer.

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Benefits Of Using Reporting and Analytics Tools in Small Businesses

Smart Data Collective

As a small business owner, you might think that data reporting and analytics don’t matter in your organization. You could be mistaken for thinking there’s too little data to report and analyze and that you can’t possibly have access to the powerful analytics tools that large businesses have. However, if you’re a small business owner looking to scale and grow, smart technology can revolutionize the way you view and understand your business.

Reporting 114
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Neural Network For Classification with Tensorflow

Analytics Vidhya

This article was published as a part of the Data Science Blogathon In this article, I am going to build neural network models with TensorFlow to solve a classification problem. Let’s explore together that how we can approach a classification problem in Tensorflow. But firstly, I would like to make sure that we are able to […]. The post Neural Network For Classification with Tensorflow appeared first on Analytics Vidhya.

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The Future of AI and ROI for the Enterprise

Dataiku

For many years, AI was an experimental risk for companies. Today, AI is not a brand new concept and most enterprises have at least explored AI implementation. As of 2020, 68% of enterprises had used AI, having already adopted AI applications or introduced AI on some level into their business processes. So, where does AI stand moving forward? Recently, Dataiku spoke with Mike Gualtieri, VP & Principal Analyst at Forrester , in “The Future of AI and ROI for the Enterprise, featuring Forrester”

ROI 110
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The Path to Product Excellence: Avoiding Common Pitfalls and Enhancing Communication

Speaker: David Bard, Principal at VP Product Coaching

In the fast-paced world of digital innovation, success is often accompanied by a multitude of challenges - like the pitfalls lurking at every turn, threatening to derail the most promising projects. But fret not, this webinar is your key to effective product development! Join us for an enlightening session to empower you to lead your team to greater heights.

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Easy Synthetic Data in Python with Faker

KDnuggets

Faker is a Python library that generates fake data to supplement or take the place of real world data. See how it can be used for data science.

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Understanding the Importance of AI in 3D Printing Applications

Smart Data Collective

Artificial intelligence has had a massive influence on the future of the manufacturing sector. Manufacturers spent over $1.1 billion on AI in 2020. That figure is likely to rise much higher in the near future. One of the biggest reasons manufacturers are investing in AI is that it has led to new advances in automation. We covered this briefly in our article about the role of AI in the evolution of robotics in manufacturing.

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An Introduction to Chatbot Development using RASA

Analytics Vidhya

This article was published as a part of the Data Science Blogathon Introduction Do you ever wonder how Google assistant, Siri, chatbots in different websites work? The advancement in the field of Natural Language Processing paves the way to different very accurate AI assistants in various fields like medical, defense, management, etc. There are several AI […].

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GraphDB Users Ask: What Does The “Insufficient Free Heap Memory” Error Mean?

Ontotext

ONTOTEXT ANSWER: This error is relatively common. This is a guard functionality of GraphDB. It is intended to prevent Out of Memory (OOM) exceptions. When evaluating “distinct”, the database has to keep a lot of data in memory. This is why it is being monitored. The easy way to fix the problem would be to give GraphDB more memory. For details on what happens, read on.

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Reimagined: Building Products with Generative AI

“Reimagined: Building Products with Generative AI” is an extensive guide for integrating generative AI into product strategy and careers featuring over 150 real-world examples, 30 case studies, and 20+ frameworks, and endorsed by over 20 leading AI and product executives, inventors, entrepreneurs, and researchers.

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Build a Serverless News Data Pipeline using ML on AWS Cloud

KDnuggets

This is the guide on how to build a serverless data pipeline on AWS with a Machine Learning model deployed as a Sagemaker endpoint.

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Beginners Guide to Using Analytics to Invest in Stocks

Smart Data Collective

Data analytics has become a crucial element of the financial industry. Financial institutions such as mutual funds and insurance companies are using big data to improve their operations. The market for financial analytics services is expected to be worth $14 billion by 2026. However, large financial organizations aren’t the only ones relying on big data technology.

Analytics 109
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Analytics Vidhya Presents INTERN-A-THON: Your First Step to Enter the Data Science World

Analytics Vidhya

Internships, uh?!! Such a stunning word for one of the most difficult tasks. In every industry, there exists a disparity when it comes to internships opportunities and getting into one. Especially in this era where competition is at its peak and opportunities for freshers close to nil. With the data industry evolving and becoming more […]. The post Analytics Vidhya Presents INTERN-A-THON: Your First Step to Enter the Data Science World appeared first on Analytics Vidhya.

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Do We Still Need Humans in the Loop for AI?

Dataiku

Automation is a fantastic and scary word. We hear about it in the press with robots doing jobs in manufacturing that people used to do. Robotic process automation (RPA) software captures and automates repetitive business tasks. In many cases, machines and software are better suited to these repetitive jobs — they don't get bored, they deliver consistent quality, and they don't leave or demand a transfer to a better paying, more exciting job.

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The Big Payoff of Application Analytics

Outdated or absent analytics won’t cut it in today’s data-driven applications – not for your end users, your development team, or your business. That’s what drove the five companies in this e-book to change their approach to analytics. Download this e-book to learn about the unique problems each company faced and how they achieved huge returns beyond expectation by embedding analytics into applications.