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.

Data Science 400

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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 367

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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.

Artificial Intelligence 254

Artificial Intelligence Artificial Intelligence Computer Science Computer Science 254

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.

Cloud Computing 130

Cloud Computing Data Pipeline AWS Database 130

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Generative AI is upending the way product developers & end-users alike are interacting with data. Despite the potential of AI, many are left with questions about the future of product development: How will AI impact my business and contribute to its success? What can product managers and developers expect in the future with the widespread adoption of AI?

AI

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.

Data Science 391

Data Science Data Scientist 391

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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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

DECEMBER 1, 2022

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

Machine Learning 391

Machine Learning Machine Learning 391

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 334

Data Science Analytics Analytics 334

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.

Data Mining 235

Data Mining Data Mining Data Mining ML 235

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Many organizations today are unlocking the power of their data by using graph databases to feed downstream analytics, enahance visualizations, and more. Yet, when different graph nodes represent the same entity, graphs get messy. Watch this essential video with Senzing CEO Jeff Jonas on how adding entity resolution to a graph database condenses network graphs to improve analytics and save your analysts time.

Database

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

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 285

Data Science 285

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 318

Data Science Analytics Analytics 318

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: Scott Sehlhorst

We know we want to create products which our customers find to be valuable. Whether we label it as customer-centric or product-led depends on how long we've been doing product management. There are three challenges we face when doing this. The obvious challenge is figuring out what our users need; the non-obvious challenges are in creating a shared understanding of those needs and in sensing if what we're doing is meeting those needs.

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.

Data Pipeline 130

Data Pipeline Data Quality Data Preparation Data Governance 130

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 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 312

Data Science Analytics Analytics 312

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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AI AI Artificial Intelligence Artificial Intelligence 203

Speaker: Timothy Chan, PhD., Head of Data Science

Are you ready to move beyond the basics and take a deep dive into the cutting-edge techniques that are reshaping the landscape of experimentation? 🌐 From Sequential Testing to Multi-Armed Bandits, Switchback Experiments to Stratified Sampling, Timothy Chan, Data Science Lead, is here to unravel the mysteries of these powerful methodologies that are revolutionizing how we approach testing.

Data Science

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 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 308

Data Science Analytics Analytics Deep Learning 308

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.

Algorithm 203

Algorithm AI AI Artificial Intelligence 203

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Start-ups & SMBs launching products quickly must bundle dashboards, reports, & self-service analytics into apps. Customers expect rapid value from your product (time-to-value), data security, and access to advanced capabilities. Traditional Business Intelligence (BI) tools can provide valuable data analysis capabilities, but they have a barrier to entry that can stop small and midsize businesses from capitalizing on them.

Analytics

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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Big Data Big Data Natural Language Processing Artificial Intelligence 139

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 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 […].

Analytics 303

Analytics Analytics Data Science Data Visualization 303

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: Kevin Kai Wong, President of Emergent Energy Solutions

In today's industrial landscape, the pursuit of sustainable energy optimization and decarbonization has become paramount. Manufacturing corporations across the U.S. are facing the urgent need to align with decarbonization goals while enhancing efficiency and productivity. Unfortunately, the lack of comprehensive energy data poses a significant challenge for manufacturing managers striving to meet their targets.

Analytics

Cassie Kozyrkov

NOVEMBER 30, 2022

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

Hypothesis Testing 130

Hypothesis Testing Data Science Machine Learning Machine Learning 130

KDnuggets

DECEMBER 2, 2022

Personalized learning, smart grading, skill gap assessment, and better ROI: The importance of incorporating Machine Learning in Online Learning cannot be overstated.

Machine Learning 294

Machine Learning Machine Learning 294

Analytics Vidhya

NOVEMBER 28, 2022

This article was published as a part of the Data Science Blogathon. Introduction Web3 is being heralded as the internet’s future. This new blockchain-based web’s vision includes cryptocurrencies, NFTs, DAOs, decentralized finance, and other features. It provides a read/write/own version of the web to which users have a monetary stake in and greater control over […].

Data Science 299

Data Science Analytics Analytics Artificial Intelligence 299

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.

Internet of Things 132

Internet of Things 132

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.