Sat.Jan 22, 2022 - Fri.Jan 28, 2022

article thumbnail

3 Reasons Why Data Scientists Should Use LightGBM

KDnuggets

There are many great boosting Python libraries for data scientists to reap the benefits of. In this article, the author discusses LightGBM benefits and how they are specific to your data science job.

article thumbnail

Introductory note on Deep Learning

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction to Deep Learning Artificial Intelligence, deep learning, machine learning?—?whatever you’re doing if you don’t understand it?—?learn it. Because otherwise you’re going to be a dinosaur within 3 years. -Mark Cuban This statement from Mark Cuban might sound drastic – but its message is […].

Insiders

Sign Up for our Newsletter

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

Trending Sources

article thumbnail

Use the Cloud More Creatively

Data Virtualization

Reading Time: 3 minutes Most organizations are moving their IT systems to the cloud. In most cases, they are performing these migrations to increase the scalability of both processing and storage, and generally to free the organization from the limitations of on-premises systems. However, The post Use the Cloud More Creatively appeared first on Data Virtualization blog - Data Integration and Modern Data Management Articles, Analysis and Information.

article thumbnail

Fire Your Super-Smart Data Consultants with DataOps

DataKitchen

Analytics are prone to frequent data errors and deployment of analytics is slow and laborious. The strategic value of analytics is widely recognized, but the turnaround time of analytics teams typically can’t support the decision-making needs of executives coping with fast-paced market conditions. Perhaps it is no surprise that the average tenure of a CDO or CAO is only about 2.5 years.

article thumbnail

How To Get Promoted In Product Management

Speaker: John Mansour

If you're looking to advance your career in product management, there are more options than just climbing the management ladder. Join our upcoming webinar to learn about highly rewarding career paths that don't involve management responsibilities. We'll cover both career tracks and provide tips on how to position yourself for success in the one that's right for you.

article thumbnail

The Best Python Courses: An Analysis Summary

KDnuggets

What does the data reveal if we ask: "What are the 10 Best Python Courses?". Collecting almost all of the courses from top platforms shows there are plenty to choose from, with over 3000 offerings. This article summarizes my analysis and presents the top three courses.

160
160
article thumbnail

A Basic Guide To Kubernetes in Production

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Modern applications are popularly made using container orchestration systems and microservice architecture. In 2014, the first echoes of the word Kubernetes in tech were heard, and the conquest of Kubernetes is due in no small amount to its flexibility and authority. Back […].

More Trending

article thumbnail

Why Choose a Hybrid Data Cloud in Financial Services?

Cloudera

As I meet with our customers, there are always a range of discussions regarding the use of the cloud for financial services data and analytics. Customers vary widely on the topic of public cloud – what data sources, what use cases are right for public cloud deployments – beyond sandbox, experimentation efforts. Private cloud continues to gain traction with firms realizing the benefits of greater flexibility and dynamic scalability.

article thumbnail

How to Set Up Your Data Science Stack on a Budget

KDnuggets

Whether you’re working independently or setting up a stack for a company, you need an affordable stack option. Here’s how you can set up your stack without spending too much.

article thumbnail

Underrated Apriori Algorithm Based Unsupervised Machine Learning

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Hello there, learners. I hope everyone is doing well. This pandemic provides us with more opportunities to learn new topics through the work-from-home concept, allowing us to devote more time to doing so. This prompted me to consider some mundane but intriguing topics. […].

article thumbnail

Artificial Intelligence Is Influencing Everyday Lives for the Better

Smart Data Collective

Artificial intelligence is having a larger impact on our lives than you may think. Although only 38% of businesses use AI in some form , 90% of the most successful companies utilize some form of AI. You may be wondering how significant AI really is. To some, AI may seem like any other over-hyped buzzword that has never truly manifested in the day-to-day human life.

article thumbnail

Navigating the Future: Generative AI, Application Analytics, and Data

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?

article thumbnail

Three Ways Integrated Data Can Deliver Outstanding Customer Experience

Teradata

The use of integrated data to restore customer confidence will be big in 2022. Building a customer insights foundation should be high on the to-do list for retail & CPG businesses this year.

105
105
article thumbnail

Getting Started Cleaning Data

KDnuggets

In order to achieve quality data, there is a process that needs to happen. That process is data cleaning. Learn more about the various stages of this process.

article thumbnail

Deploying ML Models Using Kubernetes

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction A Machine Learning solution to an unambiguously defined business problem is developed by a Data Scientist ot ML Engineer. The Model development process undergoes multiple iterations and finally, a model which has acceptable performance metrics on test data is taken to the production […].

Modeling 341
article thumbnail

Optimizing Your IT Budget While Running a Data-Centric Company

Smart Data Collective

Big data technology has become a very important aspect of our lives. More businesses than ever are transitioning to data-driven business models. Research has shown that companies with big data strategies are 19 times more likely to become profitable. Unfortunately, some businesses have made poor decisions when instituting a data strategy. In a sense, despite its tremendous value, big data has become a bit of a bubble for many companies.

article thumbnail

Get Better Network Graphs & Save Analysts Time

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.

article thumbnail

Polars - A lightning fast DataFrames library

Domino Data Lab

We have previously talked about the challenges that the latest SOTA models present in terms of computational complexity. We've also talked about frameworks like Spark, Dask, and Ray , and how they help address this challenge using parallelization and GPU acceleration.

article thumbnail

R vs Python (Again): A Human Factor Perspective

KDnuggets

This post is tentative to explain by "human factor" - a typical Python vs. R user, the widespread opinion that Python is better suited than R for developing production-quality code.

110
110
article thumbnail

A Detailed Guide for Data Handling Techniques in Data Science

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Image Source: Author Introduction Data Engineers and Data Scientists need data for their Day-to-Day job. Of course, It could be for Data Analytics, Data Prediction, Data Mining, Building Machine Learning Models Etc., All these are taken care of by the respective team members and […].

article thumbnail

Editing Guide for AI-Driven YouTube Video Creators

Smart Data Collective

There are a lot of benefits of using artificial intelligence in 2022. One of the biggest reasons that many people use AI is to improve their marketing strategies. A recent survey found that 64% of marketers reported that data-driven marketing strategies are more important than ever. One of the biggest reasons big data is so useful is that it helps supplement AI technology.

article thumbnail

Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You Need to Know

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.

article thumbnail

Top 4 Ways to Improve Storage Performance and Increase Agility

CDW Research Hub

Understanding storage performance is a significant factor in determining the efficiency and longevity of an organization’s infrastructure. In today’s data-driven world, your storage architecture must be able to store, protect and manage all sources and types of data while scaling to manage the exponential growth of data created by IoT, videos, photos, files, and apps.

article thumbnail

KDnuggetsâ„¢ News 22:n04, Jan 26: The High Paying Side Hustles for Data Scientists; Top Programming Languages and Their Uses

KDnuggets

The High Paying Side Hustles for Data Scientists; Top Programming Languages and Their Uses; Artificial Intelligence Project Ideas for 2022; The Best Python Courses: An Analysis Summary; Top Stories, Jan 17-23: The High Paying Side Hustles for Data Scientists.

106
106
article thumbnail

Feedforward Neural Network: Its Layers, Functions, and Importance

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Feedforward Neural Networks, also known as Deep feedforward Networks or Multi-layer Perceptrons, are the focus of this article. For example, Convolutional and Recurrent Neural Networks (which are used extensively in computer vision applications) are based on these networks.

IT 306
article thumbnail

Businesses Find Brilliant New Ways to Leverage the Power of Data

Smart Data Collective

Big data is undoubtedly changing the future of modern business. One study from KPMG found that 70% of businesses feel their big data initiatives are going to be invaluable to the future of their business model. How they choose to leverage their data is going to be vital to their future success. Smart Businesses Search for New Ways to Leverage Big Data.

article thumbnail

Understanding User Needs and Satisfying Them

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.

article thumbnail

96 Percent of Businesses Can’t Be Wrong: How Hybrid Cloud Came to Dominate the Data Sector

Cloudera

According to 451 Research , 96% of enterprises are actively pursuing a hybrid IT strategy. Modern, real-time businesses require accelerated cycles of innovation that are expensive and difficult to maintain with legacy data platforms. Cloud technologies and respective service providers have evolved solutions to address these challenges. . The hybrid cloud’s premise—two data architectures fused together—gives companies options to leverage those solutions and to address decision-making criteria, on

article thumbnail

TensorFlow for Computer Vision – Transfer Learning Made Easy

KDnuggets

In this article, see how you can get above 90% accuracy on the validation set with a pretty straightforward approach. You'll also see what happens to the validation accuracy if we scale down the amount of training data by a factor of 20. Spoiler alert - it will remain unchanged.

IT 106
article thumbnail

A Beginner’s Introduction to starting out with Scala

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. [link] Index 1) Introduction 2) Installation 3) Writing code with Scala What is Scala? Scala is a high-level language that combines the paradigms of both functional and object-oriented programming, which makes it powerful. It is used by tech giants like Netflix, Twitter, and […].

article thumbnail

Securing Venture Capital for Your New Cloud Startup

Smart Data Collective

Are you trying to grow or launch a cloud technology startup? You won’t be able to do so without a significant amount of capital. Recent news reports on Infracost can give you some insights on the cost of launching a cloud startup. This company raised over $2.2 million in funding to grow its operations. Of course, they had to spend a lot more money to start their business in the first place.

article thumbnail

How Embedded Analytics Gets You to Market Faster with a SAAS Offering

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.

article thumbnail

Customizing Personal Lines Insurance with Location Data

Cloudera

Insurers are increasingly adopting data from smart devices and related technologies to support and service their customers better. According to Statista , the projected installed base of IOT devices is expected to increase to 30.9 billion units by 2025, a huge jump from the 13.8 billion units that exist today. I have been researching more about how we can use the new data from those devices to design more innovative insurance products while being aware that these should all be contingent upon cu

article thumbnail

Learn Machine Learning 4X Faster by Participating in Competitions

KDnuggets

Participating in competitions has taught me everything about machine learning and how It can help you learn multiple domains faster than online courses.

article thumbnail

A Comprehensive Guide on Neo4j

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Today, most organizations invest more than ever in their resources to finely leverage graph analytics to extract valuable insights from massive, complex volumes of data. For those who don’t know, Neo4j is one of the most popular graph databases that gives developers and data […].

article thumbnail

Academic Research Done on Alluvial Diagrams

The Data Visualisation Catalogue

For this website, I’ve started to compile a list of academic papers and any related articles that study or use a particular type of visualisation. I thought it would be a good idea to share what I have found since there isn’t a resource (that I know of), which list papers and journal articles by chart type. So this entry, I will be listing and briefly reviewing all the research I’ve found on Alluvial Diagrams.

article thumbnail

Manufacturing Sustainability Surge: Your Guide to Data-Driven Energy Optimization & Decarbonization

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.