KDnuggets
DECEMBER 19, 2022
RPA and IA have stunned the business world by availing impressive, intelligent automation capabilities for scales of businesses across industries, which we'll know in this blog.
Dataversity
OCTOBER 2, 2022
AI models have been proven to enhance critical processes that influence bottom lines, from predicting and preventing churn to detecting instances of fraud. But AI has also made headlines for producing harmful business and societal results, such as discriminating against individuals based on race or gender.
FlowingData
DECEMBER 29, 2022
Every year, I pick my favorite data visualization projects, which tend to cover a wide range of purposes but are typically for presentation. Here are my favorites for 2022. Read More.
DataRobot Blog
DECEMBER 6, 2022
Savvy data scientists are already applying artificial intelligence and machine learning to accelerate the scope and scale of data-driven decisions in strategic organizations. These data science teams are seeing tremendous results—millions of dollars saved, new customers acquired, and new innovations that create a competitive advantage. Other organizations are just discovering how to apply AI to accelerate experimentation time frames and find the best models to produce results.
Speaker: Dr. Greg Loughnane and Chris Alexiuk
Technology professionals developing generative AI applications are finding that there are big leaps from POCs and MVPs to production-ready applications. They're often developing using prompting, Retrieval Augmented Generation (RAG), and fine-tuning (up to and including Reinforcement Learning with Human Feedback (RLHF)), typically in that order. However, during development – and even more so once deployed to production – best practices for operating and improving generative AI applications are le
Hacker News
OCTOBER 20, 2022
Pretty much all the practitioners I favor in Software Architecture are deeply suspicious of any kind of general law in the field. Good software architecture is very context-specific, analyzing trade-offs that resolve differently across a wide range of environments. But if there is one thing they all agree on, it's the importance and power of Conway's Law.
Data Science Current brings together the best content for data science professionals from the widest variety of thought leaders.
Analytics Vidhya
APRIL 14, 2022
This article was published as a part of the Data Science Blogathon. Source: Forbes.com Introduction It is not hidden from the audience that quantum computing is the future of data processing. Tech giants like IBM, Google, and Microsoft are all aggressively pursuing quantum computing technology for a good reason. The massive speedups and power savings of quantum […].
The Data Administration Newsletter
FEBRUARY 16, 2022
No, this is not a mistyping of data literacy. Yes, like everyone, I am aware of and fully on-board with the growing movement to improve data literacy in the enterprise. What I want to talk about is Data Littering, which is something else entirely. Data Littering is the deliberate act of creating and distributing data […].
DataRobot
JANUARY 20, 2022
Shifting to Proactive Healthcare Delivery with AI. The Case for Change. The UK Government Health and Care Bill sets up Integrated Care Systems (ICSs) as legal entities from July 2022. While ICSs have been operating in shadow-format for a number of years, this long-awaited shift determines that health and care delivery in England is regionally managed and focused around the needs of the local population.
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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Dataconomy
DECEMBER 28, 2022
Artificial intelligence (AI) has the potential to revolutionize the way we drive and transport goods and people. Self-driving cars, also known as autonomous vehicles, are a type of vehicle that use AI and other advanced technologies to navigate roads and highways without the need for a human driver. There are several benefits to self-driving cars. […].
KDnuggets
DECEMBER 30, 2022
Data science is ever-evolving, so mastering its foundational technical and soft skills will help you be successful in a career as a Data Scientist, as well as pursue advance concepts, such as deep learning and artificial intelligence.
KDnuggets
DECEMBER 30, 2022
It's time again to look at some data science cheatsheets. Here you can find a short selection of such resources which can cater to different existing levels of knowledge and breadth of topics of interest.
KDnuggets
DECEMBER 16, 2022
Many aspiring Data Scientists, especially when self-learning, fail to learn the necessary math foundations. These recommendations for learning approaches along with references to valuable resources can help you overcome a personal sense of not being "the math type" or belief that you "always failed in math.".
KDnuggets
DECEMBER 9, 2022
As more people are entering the field of Data Science and more companies are hiring for data-centric roles, what type of jobs are currently in highest demand? There is so much data in the world, and it just keeps flooding in, it now looks like companies are targeting those who can engineer that data more than those who can only model the data.
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.
KDnuggets
AUGUST 24, 2022
This blog post introduces seven techniques that are commonly applied in domains like intrusion detection or real-time bidding, because the datasets are often extremely imbalanced.
KDnuggets
NOVEMBER 23, 2022
There exist so many great computational tools available for Data Scientists to perform their work. However, mathematical skills are still essential in data science and machine learning because these tools will only be black-boxes for which you will not be able to ask core analytical questions without a theoretical foundation.
KDnuggets
NOVEMBER 18, 2022
The Pandas library is core to any Data Science work in Python. This introduction will walk you through the basics of data manipulating, and features many of Pandas important features.
KDnuggets
NOVEMBER 16, 2022
While different ways to learn Data Science for the first time exist, the approach that works for you should be based on how you learn best. One powerful method is to evolve your learning from simple practice into complex foundations, as outlined in this learning path recommended by a physicist who turned into a Data Scientist.
KDnuggets
OCTOBER 24, 2022
Preprocessing data for machine learning models is a core general skill for any Data Scientist or Machine Learning Engineer. Follow this guide using Pandas and Scikit-learn to improve your techniques and make sure your data leads to the best possible outcome.
KDnuggets
SEPTEMBER 1, 2022
Subset selection is one of the most frequently performed tasks while manipulating data. Pandas provides different ways to efficiently select subsets of data from your DataFrame.
KDnuggets
OCTOBER 19, 2022
This post is a summary of 2 distinct frameworks for approaching machine learning tasks, followed by a distilled third. Do they differ considerably (or at all) from each other, or from other such processes available?
KDnuggets
MAY 26, 2022
Read the best books on Machine Learning, Deep Learning, Computer Vision, Natural Language Processing, MLOps, Robotics, IoT, AI Products Management, and Data Science for Executives.
KDnuggets
OCTOBER 14, 2022
Leveraging sparse matrix representations for your data when appropriate can spare you memory storage. Have a look at the reasons why, see how to create sparse matrices in with Python, and compare the memory requirements for standard and sparse representations of the same data.
KDnuggets
OCTOBER 11, 2022
A Data Science Enablement Team consists of people from various departments like marketing, sales, product development, etc. They are responsible for providing the necessary tools and resources to help the data scientists do their job more efficiently.
KDnuggets
OCTOBER 7, 2022
There is no shortage of tools today that can help you through the steps of natural language processing, but if you want to get a handle on the basics this is a good place to start. Read about the ABCs of NLP, all the way from A to Z.
KDnuggets
OCTOBER 12, 2022
Do you want to learn PyTorch for machine learning and deep learning? Check out this 24 hour long video course with accompanying notes and courseware for free. Did I mention it's free?
KDnuggets
OCTOBER 10, 2022
The only cheat you need for a job interview and data professional life. It includes SQL, web scraping, statistics, data wrangling and visualization, business intelligence, machine learning, deep learning, NLP, and super cheat sheets.
KDnuggets
SEPTEMBER 20, 2022
When building and optimizing your classification model, measuring how accurately it predicts your expected outcome is crucial. However, this metric alone is never the entire story, as it can still offer misleading results. That's where these additional performance evaluations come into play to help tease out more meaning from your model.
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