KDnuggets

DECEMBER 1, 2022

In this blog, I shared my story on getting 4 data science job offers including Airbnb, Lyft and Twitter after being laid off. Any data scientist who was laid off due to the pandemic or who is actively looking for a data science position can find something here to which they can relate.

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Analytics Vidhya

NOVEMBER 27, 2022

This article was published as a part of the Data Science Blogathon. Source: totaljobs.com Introduction Until recently, developing new, improved transformers specifically for a single modality was common practice. However, to tackle real-world tasks, there was a pressing need to develop multi-modal transformers models. Multi-modal transformers models are the type of models that employ the […].

Data Science 380

Data Science Analytics Analytics Data Engineer 380

Dataconomy

NOVEMBER 28, 2022

It’s really important to discuss the benefits and drawbacks of artificial intelligence before it gets out of hand because this technology is improving and evolving at such a pace. As a computer science field, AI focuses on developing software and machines that mimic human thinking. Some artificial intelligence systems can.

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Adrian Bridgwater for Forbes

DECEMBER 1, 2022

What businesses need from cloud computing is the power to work on their data without having to transport it around between different clouds, different databases and different repositories, different integrations to third-party applications, different data pipelines and different compute engines.

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Many software teams have migrated their testing and production workloads to the cloud, yet development environments often remain tied to outdated local setups, limiting efficiency and growth. This is where Coder comes in. In our 101 Coder webinar, you’ll explore how cloud-based development environments can unlock new levels of productivity. Discover how to transition from local setups to a secure, cloud-powered ecosystem with ease.

KDnuggets

DECEMBER 2, 2022

The data science field is full of job opportunities, yet there is still a lot of confusion about what data scientists actually do. This confusion is largely due to the many myths that exist about the role of a data scientist. In this article, we will bust the top 10 myths about data science. By the end of this article, you will have a better understanding of the role of a data scientist and what it takes to be one.

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Data Science Data Scientist 398

Analytics Vidhya

NOVEMBER 27, 2022

This article was published as a part of the Data Science Blogathon. Introduction Which language do we use when it comes to data analysis? Of course, Python, isn’t it? But there is one more language for data analysis which is growing rapidly. Some of you might guess the language – I am talking about Julia. […]. The post An Introduction to Julia for Data Analysis appeared first on Analytics Vidhya.

Data Analysis 380

Data Analysis Data Analysis Data Science Python 380

Machine Learning Research at Apple

NOVEMBER 30, 2022

Multi-lingual language models (LM), such as mBERT, XLM-R, mT5, mBART, have been remarkably successful in enabling natural language tasks in low-resource languages through cross-lingual transfer from high-resource ones. In this work, we try to better understand how such models, specifically mT5, transfer any linguistic and semantic knowledge across languages, even though no explicit cross-lingual signals are provided during pre-training.

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KDnuggets

NOVEMBER 30, 2022

The best way to learn Data Science is by solving real-world problems with the data and building your own portfolio. In this article, we will discuss three projects that you can work on to build your portfolio and impress interviewers.

Data Science 300

Data Science 300

Analytics Vidhya

DECEMBER 2, 2022

This article was published as a part of the Data Science Blogathon. Introduction K nearest neighbors are one of the most popular and best-performing algorithms in supervised machine learning. Furthermore, the KNN algorithm is the most widely used algorithm among all the other algorithms developed due to its speed and accurate results. Therefore, the data […].

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Dataconomy

NOVEMBER 29, 2022

In the modern world, obtaining data is easier than ever, but generating insights and information from that data is becoming more challenging. Businesses regularly find themselves in a situation where they have far more data than they know what to do with, which may be counterproductive and lead to inaction.

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Large enterprises face unique challenges in optimizing their Business Intelligence (BI) output due to the sheer scale and complexity of their operations. Unlike smaller organizations, where basic BI features and simple dashboards might suffice, enterprises must manage vast amounts of data from diverse sources. What are the top modern BI use cases for enterprise businesses to help you get a leg up on the competition?

Business Intelligence

Adrian Bridgwater for Forbes

NOVEMBER 29, 2022

As we continue to try and work out where technology should best be applied to elevate us up and away from the forces of disruption that still circle, there is perhaps a natural temptation to look for macro-level trends, but could an SME focus also help?

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KDnuggets

DECEMBER 1, 2022

The latest KDnuggets exclusive cheatsheet covers the essentials of machine learning with Scikit-learn.

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Analytics Vidhya

NOVEMBER 30, 2022

This article was published as a part of the Data Science Blogathon. Introduction Source: Image by Gerd Altmann from Pixabay Smart contracts are blockchain-based computer programs that activate at predefined times. In most cases, they are used to eliminate the need for a third party during the execution of a contract, allowing all parties to […].

Data Science 345

Data Science Analytics Analytics 345

Dataconomy

NOVEMBER 28, 2022

If you use the popular instant messaging service, your data could be for sale in the latest dark web WhatsApp data leak. No official report on whether anyone has exploited the exposed user data exists.

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Speaker: Mike Rizzo, Founder & CEO, MarketingOps.com and Darrell Alfonso, Director of Marketing Strategy and Operations, Indeed.com

Though rarely in the spotlight, marketing operations are the backbone of the efficiency, scalability, and alignment that define top-performing marketing teams. In this exclusive webinar led by industry visionaries Mike Rizzo and Darrell Alfonso, we’re giving marketing operations the recognition they deserve! We will dive into the 7 P Model —a powerful framework designed to assess and optimize your marketing operations function.

IBM Data Science in Practice

NOVEMBER 28, 2022

As organizations steer their business strategies to become data-driven decision-making organizations, data and analytics are more crucial than ever before. Insights from data gathered across business units improve business outcomes, but having heterogeneous data from disparate applications and storages makes it difficult for organizations to paint a big picture.

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KDnuggets

NOVEMBER 29, 2022

First steps to learning data science & machine learning are the foundations.

Machine Learning 400

Machine Learning Machine Learning Data Science 400

Analytics Vidhya

NOVEMBER 30, 2022

This article was published as a part of the Data Science Blogathon. Introduction Let’s say you want to build Dapp on top of the blockchain. So you wrote the code and configured your specification. Now you need to deploy it on the blockchain. But wait, you need to download the entire network to do so! […]. The post Dapp Deployment Using Quick Node RPC appeared first on Analytics Vidhya.

Data Science 335

Data Science Analytics Analytics 335

Dataconomy

DECEMBER 2, 2022

Lensa AI selfie generator is taking social media by storm. Internet users have been using a wide range of filters to edit their photographs for years, whether adding a virtual mask to their faces or making their backgrounds look exotic. Now, they have a new option called Lensa AI. Lensa.

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Speaker: Jay Allardyce, Deepak Vittal, and Terrence Sheflin

As we look ahead to 2025, business intelligence and data analytics are set to play pivotal roles in shaping success. Organizations are already starting to face a host of transformative trends as the year comes to a close, including the integration of AI in data analytics, an increased emphasis on real-time data insights, and the growing importance of user experience in BI solutions.

Business Intelligence

Cassie Kozyrkov

NOVEMBER 27, 2022

Introduction to “good” statistical estimators and their properties Continue reading on Towards Data Science »

Data Science 130

Data Science Artificial Intelligence Artificial Intelligence Machine Learning 130

KDnuggets

DECEMBER 1, 2022

Introduction to PyTorch Lightning and how it can be used for the model building process. It also provides a brief overview of the PyTorch characteristics and how they are different from TensorFlow.

Machine Learning 271

Machine Learning Machine Learning 271

Analytics Vidhya

NOVEMBER 30, 2022

This article was published as a part of the Data Science Blogathon. Introduction Hey, are you working on a data science project, solving a problem statement related to data science, or experimenting with a statistical test to make further decisions and handling the most repeatedly cited statistical term, ‘correlation’? Willing to correctly interpret these statistical […].

Data Science 330

Data Science Analytics Analytics 330

Dataconomy

DECEMBER 1, 2022

The OpenAI ChatGPT chatbot was just released and is already quite popular. Say hello to the newest chatbot with one of the most advanced AI algorithms. You will wonder if you’re speaking to a human or a chatbot from time to time with ChatGPT. OpenAI is making a chatbot available.

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Algorithm AI AI Artificial Intelligence 203

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Cloud Development Environments (CDEs) are changing how software teams work by moving development to the cloud. Our Cloud Development Environment Adoption Report gathers insights from 223 developers and business leaders, uncovering key trends in CDE adoption. With 66% of large organizations already using CDEs, these platforms are quickly becoming essential to modern development practices.

Smart Data Collective

DECEMBER 1, 2022

The world of big data is constantly changing and evolving, and 2021 is no different. As we look ahead to 2022, there are four key trends that organizations should be aware of when it comes to big data: cloud computing, artificial intelligence, automated streaming analytics, and edge computing. Each of these trends will continue to shape the way companies use data in the coming years.

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KDnuggets

NOVEMBER 29, 2022

What is Chebychev's Theorem and How Does it Apply to Data Science? • How to Select Rows and Columns in Pandas Using [ ],loc, iloc,at and.iat • Linux for Data Science Cheatsheet • How Much Math Do You Need in Data Science? • Git for Data Science Cheatsheet.

Data Science 271

Data Science 271

Analytics Vidhya

NOVEMBER 27, 2022

This article was published as a part of the Data Science Blogathon. Source: DDI Introduction Autoencoders are an unsupervised model that takes unlabeled data and learns effective coding about the data structure that can be applied to another context. It approximates the function that maps the data from input space to lower dimensional coordinates and […].

Data Science 327

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Dataconomy

DECEMBER 2, 2022

Cloud automation can help reduce mistakes and errors and take away the monotony of doing the same things over and over again. Cloud automation is encouraged by good cloud infrastructure. One of the primary drivers for putting it into practice is actually this. Even though cloud computing has been a.

Cloud Computing 193

Cloud Computing 193

Speaker: Nikhil Joshi, Founder & President of Snic Solutions

Is your manufacturing operation reaching its efficiency potential? A Manufacturing Execution System (MES) could be the game-changer, helping you reduce waste, cut costs, and lower your carbon footprint. Join Nikhil Joshi, Founder & President of Snic Solutions, in this value-packed webinar as he breaks down how MES can drive operational excellence and sustainability.

Cassie Kozyrkov

NOVEMBER 30, 2022

A primer on interpreting other people’s hypothesis tests Continue reading on Towards Data Science »

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Hypothesis Testing Data Science Machine Learning Machine Learning 130

KDnuggets

NOVEMBER 28, 2022

Everything you need to know to start your career in Data Engineering.

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Analytics Vidhya

NOVEMBER 30, 2022

This article was published as a part of the Data Science Blogathon. Introduction Data and Information about a Customer are important for all businesses and companies. For a business to be data-driven, a Company needs to be highly data-driven and focus highly on customer analytics. Information about customers can be collected from many sources. It […].

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Analytics Analytics Data Science Data Visualization 322

Dataconomy

DECEMBER 1, 2022

Nowadays we can connect everyday objects to the internet, which is only possible thanks to IoT sensors. Last month we talked about “the veins of IoT devices,” but today, we are here to discuss “the brain of IoT devices,” which are IoT sensors, because no human-made device can work without.

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Internet of Things 132

Speaker: Anindo Banerjea, CTO at Civio & Tony Karrer, CTO at Aggregage

When developing a Gen AI application, one of the most significant challenges is improving accuracy. This can be especially difficult when working with a large data corpus, and as the complexity of the task increases. The number of use cases/corner cases that the system is expected to handle essentially explodes. 💥 Anindo Banerjea is here to showcase his significant experience building AI/ML SaaS applications as he walks us through the current problems his company, Civio, is solving.

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