Search results for "banking"

151 documents found out of 7061 total.

• Are AI Browsers Any Good? A Day with Perplexity’s Comet and OpenAI’s Atlas

  Understanding the underlying technology helps explain why AI browsers exhibit such uneven performance.

  https://www.kdnuggets.com/are-ai-browsers-any-good-day-with-perplexity-comet-openai-atlas

• 10 Free Online Courses to Master Python in 2025

  How can you master Python for free? Here are ten online courses we recommend.

  https://www.kdnuggets.com/10-free-online-courses-to-master-python-in-2025

• Guardio Review 2025: Features, Pros & Cons

  Guardio is a browser extension designed to enhance online security by blocking phishing attempts, malicious websites, and harmful browser extensions. It also provides real-time data breach alerts and improves browsing by blocking intrusive ads and pop-ups. Its lightweight, user-friendly design makes it ideal for individuals and families seeking protection from browser-based threats without complex setups. While it lacks offline security and requires Gmail access for phishing detection, even the Basic version offers a solid starting point for online safety, with Premium adding comprehensive features. Guardio is a versatile solution available across all devices, including mobile, making it an excellent choice for anyone looking to enhance their online security and protect against browser-based threats.

  https://www.kdnuggets.com/review/guardio-review-2024-features-pros-cons

• How AI is Revolutionizing the Legacy Industries?

  Get ready for an exciting journey into how AI is changing the tech world!

  https://www.kdnuggets.com/how-ai-is-revolutionizing-the-legacy-industries

• Natural Language Processing: Bridging Human Communication with AI

  The post highlights real-world examples of NLP use cases across industries. It also covers NLP's objectives, challenges, and latest research developments.

  https://www.kdnuggets.com/natural-language-processing-bridging-human-communication-with-ai

• 5 Ways of Converting Unstructured Data into Structured Insights with LLMs

  From Chaos to Clarity: Understanding the Unstructured Data Dilemma.

  https://www.kdnuggets.com/5-ways-of-converting-unstructured-data-into-structured-insights-with-llms

• The Top 8 Cloud Container Management Solutions of 2024

  As enterprises rapidly adopt cloud-native technologies, managing containerized applications has become crucial, so this article provides practical insights on the leading container management solutions to help organizations choose the right one for their needs.

  https://www.kdnuggets.com/the-top-8-cloud-container-management-solutions-of-2024

• AI in Intimate Roles: Girlfriends and Therapists

  This article is a brief overview of the field of Emotion AI, and the potential applications of its technology in intimate roles.

  https://www.kdnuggets.com/ai-in-intimate-roles-girlfriends-and-therapists

• Top 10 Kaggle Machine Learning Projects to Become Data Scientist in 2024

  Master Data Science with Top 10 Kaggle ML Projects to become a Data Scientist.

  https://www.kdnuggets.com/top-10-kaggle-machine-learning-projects-to-become-data-scientist-in-2024

• Will AI Replace Humanity?

  Let’s discover whether AI is truly intelligent and has the potential to supersede humans.

  https://www.kdnuggets.com/will-ai-replace-humanity

• Parallel Processing in Prompt Engineering: The Skeleton-of-Thought Technique

  Explore how the Skeleton-of-Thought prompt engineering technique enhances generative AI by reducing latency, offering structured output, and optimizing projects.

  https://www.kdnuggets.com/parallel-processing-in-prompt-engineering-the-skeleton-of-thought-technique

• OLAP vs. OLTP: A Comparative Analysis of Data Processing Systems

  A comprehensive comparison between OLAP and OLTP systems, exploring their features, data models, performance needs, and use cases in data engineering.

  https://www.kdnuggets.com/2023/08/olap-oltp-comparative-analysis-data-processing-systems.html

• Clustering Unleashed: Understanding K-Means Clustering

  Learn how to find hidden patterns and extract meaningful insights using Unsupervised Learning with the K-Means clustering algorithm.

  https://www.kdnuggets.com/2023/07/clustering-unleashed-understanding-kmeans-clustering.html

• Ensuring Reliable Few-Shot Prompt Selection for LLMs

  Data-centric techniques for better Few-Shot Prompting when applying LLMs to Noisy Real-World Data.

  https://www.kdnuggets.com/2023/07/ensuring-reliable-fewshot-prompt-selection-llms.html

• Data access is severely lacking in most companies, and 71% believe synthetic data can help

  MOSTLY AI has conducted the first-ever synthetic data survey in the data science AI/ML community. Check out the results here.

  https://www.kdnuggets.com/2023/07/mostly-data-access-severely-lacking-synthetic-data-help.html

• Synthetic Data Platforms: Unlocking the Power of Generative AI for Structured Data

  The article highlights various use cases of synthetic data, including generating confidential data, rebalancing imbalanced data, and imputing missing data points. It also provides information on popular synthetic data generation tools such as MOSTLY AI, SDV, and YData.

  https://www.kdnuggets.com/2023/07/synthetic-data-platforms-unlocking-power-generative-ai-structured-data.html

• 5 Highest-paid Languages to Learn This Year

  Level up your coding skills by learning the hottest programming languages to boost your career and fatten your paycheck!.

  https://www.kdnuggets.com/2023/07/5-highestpaid-languages-learn-year.html

• How to MLOps like a Boss: A Guide to Machine Learning without Tears

  If you have ever emailed a .pickle file to engineers for deployment, this is for YOU!

  https://www.kdnuggets.com/2023/06/mlops-like-boss-guide-machine-learning-without-tears.html

• A Playbook to Scale MLOps

  MLOps teams are pressured to advance their capabilities to scale AI. We teamed up with Ford Motors to explore how to scale MLOps within an organization and how to get started.

  https://www.kdnuggets.com/2023/06/playbook-scale-mlops.html

• Data Analytics: The Four Approaches to Analyzing Data and How To Use Them Effectively

  You will learn about descriptive analytics, data warehousing, machine learning, and big data.

  https://www.kdnuggets.com/2023/04/data-analytics-four-approaches-analyzing-data-effectively.html

• What Are The Downsides of AI Advancement?

  While AI has certainly several positive uses to offer the world, it’s also displaying harm when it comes to academics, cybersecurity, the environment, jobs, and privacy.

  https://www.kdnuggets.com/2023/03/downsides-ai-advancement.html

• Master the Power of Data Analytics: The Four Approaches to Analyzing Data

  Learn about descriptive analytics, data warehousing, machine learning, and big data.

  https://www.kdnuggets.com/2023/03/master-power-data-analytics-four-approaches-analyzing-data.html

• SQL Query Optimization Techniques

  Learn how to optimize the queries written in SQL to make them execute faster and more memory efficient.

  https://www.kdnuggets.com/2023/03/sql-query-optimization-techniques.html

• Top 5 Advantages That CatBoost ML Brings to Your Data to Make it Purr

  This article outlines the advantages of CatBoost as a GBDTs for interpreting data sources that are highly categorical or contain missing data points.

  https://www.kdnuggets.com/2023/02/top-5-advantages-catboost-ml-brings-data-make-purr.html

• 5 Statistical Paradoxes Data Scientists Should Know

  Knowing these 5 statistical paradoxes is essential for data scientists to improve their analyses and machine learning models.

  https://www.kdnuggets.com/2023/02/5-statistical-paradoxes-data-scientists-know.html

• Hyperparameter Optimization: 10 Top Python Libraries

  Become familiar with some of the most popular Python libraries available for hyperparameter optimization.

  https://www.kdnuggets.com/2023/01/hyperparameter-optimization-10-top-python-libraries.html

• 5 Ways to Deal with the Lack of Data in Machine Learning

  Effective solutions exist when you don't have enough data for your models. While there is no perfect approach, five proven ways will get your model to production.

  https://www.kdnuggets.com/2019/06/5-ways-lack-data-machine-learning.html

• Explainable AI: 10 Python Libraries for Demystifying Your Model’s Decisions

  Become familiar with some of the most popular Python libraries available for AI explainability.

  https://www.kdnuggets.com/2023/01/explainable-ai-10-python-libraries-demystifying-decisions.html

• Creating a Web Application to Extract Topics from Audio with Python

  A step-by-step tutorial to build and deploy a web application for topic modeling of a Spotify podcast.

  https://www.kdnuggets.com/2023/01/creating-web-application-extract-topics-audio-python.html

• Telling a Great Data Story: A Visualization Decision Tree

  Pick your visualizations strategically. They need to tell a story.

  https://www.kdnuggets.com/2021/02/telling-great-data-story-visualization-decision-tree.html

• Getting Started with spaCy for NLP

  In this blog, we will explore how to get started with spaCy right from the installation to explore the various functionalities it provides.

  https://www.kdnuggets.com/2022/11/getting-started-spacy-nlp.html

• 25 Advanced SQL Interview Questions for Data Scientists

  Check out this collection of advanced SQL interview questions with answers.

  https://www.kdnuggets.com/2022/10/25-advanced-sql-interview-questions-data-scientists.html

• AI in FinTech: Managing the Finance of the Future

  Digital transformation is evolving, and so is the fintech industry by implementing AI trends and leveraging several benefits, such as optimizing productivity, increasing ROI, and enhancing security.

  https://www.kdnuggets.com/2022/10/ai-fintech-managing-finance-future.html

• 7 Techniques to Handle Imbalanced Data

  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.

  https://www.kdnuggets.com/2017/06/7-techniques-handle-imbalanced-data.html

• The Evolution From Artificial Intelligence to Machine Learning to Data Science

  By the end of this article, you should be able to distinguish between these concepts.

  https://www.kdnuggets.com/2022/08/evolution-artificial-intelligence-machine-learning-data-science.html

• How ML Model Explainability Accelerates the AI Adoption Journey for Financial Services

  Explainability and good model governance reduce risk and create the framework for ethical and transparent AI in financial services that eliminates bias.

  https://www.kdnuggets.com/2022/07/ml-model-explainability-accelerates-ai-adoption-journey-financial-services.html

• Ten Key Lessons of Implementing Recommendation Systems in Business

  We've been long working on improving the user experience in UGC products with machine learning. Following this article's advice, you will avoid a lot of mistakes when creating a recommendation system, and it will help to build a really good product.

  https://www.kdnuggets.com/2022/07/ten-key-lessons-implementing-recommendation-systems-business.html

• Top Industries and Employers Hiring Data Scientists in 2022

  This article presents the top industries and companies that are currently actively hiring data scientists.

  https://www.kdnuggets.com/2022/06/top-industries-employers-hiring-data-scientists-2022.html

• How Has the Adoption of AI in Algorithmic Trading Affected the Finance Industry?

  Algorithmic trading is the execution of trading operations according to a given algorithm. Read on to find out more.

  https://www.kdnuggets.com/2022/04/adoption-ai-algorithmic-trading-affected-finance-industry.html

• The Complete Collection Of Data Repositories – Part 1

  Check out the collection of the best data repositories on agriculture, audio, biology, climate, computer vision, economics, education, energy, finance, and government.

  https://www.kdnuggets.com/2022/04/complete-collection-data-repositories-part-1.html

• How Much Do Data Scientists Make in 2022?

  The data scientist salary - the past, the present, and a little bit of the future.

  https://www.kdnuggets.com/2022/02/much-data-scientists-make-2022.html

• Explain NLP Models with LIME

  It is important to know how LIME reaches to its final outputs for explaining a prediction done for text data. In this article, I have shared that concept by enlightening the components of LIME.

  https://www.kdnuggets.com/2022/01/explain-nlp-models-lime.html

• Top Programming Languages and Their Uses

  The landscape of programming languages is rich and expanding, which can make it tricky to focus on just one or another for your career. We highlight some of the most popular languages that are modern, widely used, and come with loads of packages or libraries that will help you be more productive and efficient in your work.

  https://www.kdnuggets.com/2021/05/top-programming-languages.html

• The Chatbot Transformation: From Failure to the Future

  The all-knowing chatbots we once thought to be the future have been replaced by specialized bots, and the results are outstanding.

  https://www.kdnuggets.com/2021/12/chatbot-transformation-failure-future.html

• Data Labeling for Machine Learning: Market Overview, Approaches, and Tools

  So much of data science and machine learning is founded on having clean and well-understood data sources that it is unsurprising that the data labeling market is growing faster than ever. Here, we highlight many of the top players in this industry and the techniques they use to help you consider which might make a good partner for your needs.

  https://www.kdnuggets.com/2021/12/data-labeling-ml-overview-and-tools.html

• Want to Join a Bank? Everything Data Scientists Need to Know About Working in Fintech

  There is ample opportunity for data scientists in the financial services sector. The career experience can be very different, however, from similar roles at pure technology organizations. So, it's best to first consider if this industry is right for your interests, preferences for how you work, and long-term goals.

  https://www.kdnuggets.com/2021/10/bank-data-scientists-working-fintech.html

• Machine Learning Model Development and Model Operations: Principles and Practices">Machine Learning Model Development and Model Operations: Principles and Practices

  The ML model management and the delivery of highly performing model is as important as the initial build of the model by choosing right dataset. The concepts around model retraining, model versioning, model deployment and model monitoring are the basis for machine learning operations (MLOps) that helps the data science teams deliver highly performing models.

  https://www.kdnuggets.com/2021/10/machine-learning-model-development-operations-principles-practice.html

• Transforming your business with SAS® Viya® on Microsoft Azure

  Faster, trusted decisions are in the cloud. See how you can use the flexibility, scalability and agility of modern technologies to advance your organization’s goals. Read our blog with 3-part video demo.

  https://www.kdnuggets.com/2021/10/sas-viya-microsoft-azure.html

• 9 Outstanding Reasons to Learn Python for Finance

  Is Python good for learning finance and working in the financial world? The answer is not only a resounding YES, but yes for nine very good reasons. This article gets into the details behind why Python is a must-know programming language for anyone who wants to work in the financial sector.

  https://www.kdnuggets.com/2021/09/9-outstanding-reasons-learn-python-finance.html

• Messy Data is Beautiful

  Once these types of data have been cleaned, they do more than show organized data sets. They reveal unlimited possibilities, and AI analytics can reveal these possibilities faster and more efficiently than ever before.

  https://www.kdnuggets.com/2021/09/sparkbeyond-messy-data-is-beautiful.html

• 6 Cool Python Libraries That I Came Across Recently

  Check out these awesome Python libraries for Machine Learning.

  https://www.kdnuggets.com/2021/09/6-cool-python-libraries-recently.html

• How is Machine Learning Beneficial in Mobile App Development?

  Mobile app developers have a lot to gain by implementing AI & Machine Learning from the revolutionary changes that these disruptive technologies can offer. This is due to AI and ML's potential to strengthen mobile applications, providing for smoother user experiences capable of leveraging powerful features.

  https://www.kdnuggets.com/2021/09/machine-learning-beneficial-mobile-app-development.html

• The Top Industries Hiring Data Scientists in 2021">The Top Industries Hiring Data Scientists in 2021

  People realize that effective uses of data can increase competitiveness, even in a challenging marketplace. Here are six industries hiring data scientists now that will likely continue doing so for the foreseeable future.

  https://www.kdnuggets.com/2021/08/top-industries-hiring-data-scientists-2021the-top-industries-hiring-data-scientists-in-2021.html

• 10 Mistakes You Should Avoid as a Data Science Beginner

  Read this article on how to gain a competitive advantage in the data science job market.

  https://www.kdnuggets.com/2021/06/10-mistakes-avoid-data-science-beginner.html

• Major changes: Where Analytics, Data Science, Machine Learning were applied in 2020/21

  Our latest poll shows major change in where AI, Data Science, Machine Learning are being applied, with decline in interest in traditional fields like CRM/Consumer Analytics, and growth in applications to Computer Vision, COVID, Agriculture, and Education.

  https://www.kdnuggets.com/2021/06/poll-where-analytics-data-science-ml-applied.html

• Data Science is Not Becoming Extinct in 10 Years, Your Skills Might

  4 reasons why data science is here to stay and what you need to do to ensure that your skillset stays in demand.

  https://www.kdnuggets.com/2021/06/data-science-not-becoming-extinct-10-years.html

• ETL in the Cloud: Transforming Big Data Analytics with Data Warehouse Automation

  Today, organizations are increasingly implementing cloud ETL tools to handle large data sets. With data sets becoming larger by the day, unified ETL tools have become crucial for data integration needs of enterprises.

  https://www.kdnuggets.com/2021/04/etl-cloud-transforming-big-data-analytics-data-warehouse-automation.html

• How to Succeed in Becoming a Freelance Data Scientist">How to Succeed in Becoming a Freelance Data Scientist

  With recent growth in data science, now is the best time to get into freelancing. The following steps will help you get started with finding clients or help you improve your current strategy.

  https://www.kdnuggets.com/2021/03/succeed-becoming-freelance-data-scientist.html

• Speech to Text with Wav2Vec 2.0

  Facebook recently introduced and open-sourced their new framework for self-supervised learning of representations from raw audio data called Wav2Vec 2.0. Learn more about it and how to use it here.

  https://www.kdnuggets.com/2021/03/speech-text-wav2vec.html

• Past 2021 Meetings / Online Events on AI, Analytics, Big Data, Data Science, and Machine Learning

  Past | Jan | Feb | Mar | Apr | May | Jun | Jul | Aug | Sep | Oct | Nov | Dec Read more »

  https://www.kdnuggets.com/meetings/past-meetings-2021.html

• Support Vector Machine for Hand Written Alphabet Recognition in R

  We attempt to break down a problem of hand written alphabet image recognition into a simple process rather than using heavy packages. This is an attempt to create the data and then build a model using Support Vector Machines for Classification.

  https://www.kdnuggets.com/2021/01/support-vector-machine-hand-written-alphabet-r.html

• Cloud Data Warehouse is The Future of Data Storage

  Today, cloud data storage accounts for 45% of all enterprise data and by Q2 2021, that number could grow to 53%. Now is the time to embrace cloud than now.

  https://www.kdnuggets.com/2021/01/cloud-data-warehouse-future-data-storage.html

• 15 Exciting AI Project Ideas for Beginners">15 Exciting AI Project Ideas for Beginners

  There are many branches to AI to learn, but a project-based approach can keep things interesting. Here is a list of 15 such projects you can get started on implementing today.

  https://www.kdnuggets.com/2020/11/greatlearning-ai-project-ideas-beginners.html

• An Introduction to AI, updated">An Introduction to AI, updated

  We provide an introduction to key concepts and methods in AI, covering Machine Learning and Deep Learning, with an updated extensive list that includes Narrow AI, Super Intelligence, and Classic Artificial Intelligence, as well as recent ideas of NeuroSymbolic AI, Neuroevolution, and Federated Learning.

  https://www.kdnuggets.com/2020/10/introduction-ai-updated.html

• How AI is Driving Innovation in Astronomy

  In this blog, we look at a disruptive AI program - Morpheus - developed by Researchers at UC Santa Cruz that can analyze astronomical image data and classify galaxies and stars with surgical precision. If you're reading this with "starry" eyes, we bet we've got you hooked.

  https://www.kdnuggets.com/2020/09/ai-driving-innovation-astronomy.html

• Top Online Masters in Analytics, Business Analytics, Data Science – Updated">Top Online Masters in Analytics, Business Analytics, Data Science – Updated

  We provide an updated list of best online Masters in AI, Analytics, and Data Science, including rankings, tuition, and duration of the education program.

  https://www.kdnuggets.com/2020/09/best-online-masters-data-science-analytics-online.html

• Rapid Python Model Deployment with FICO Xpress Insight

  The biggest hurdle in the use of data to create business value, is indeed the ability to operationalize analytics throughout the organization. Xpress Insight is geared to reduce the burden on IT and address their critical requirements while empowering business users to take ownership of decisions and change management.

  https://www.kdnuggets.com/2020/08/fico-xpress-insight-python-deployment.html

• Content-Based Recommendation System using Word Embeddings

  This article explores how average Word2Vec and TF-IDF Word2Vec can be used to build a recommendation engine.

  https://www.kdnuggets.com/2020/08/content-based-recommendation-system-word-embeddings.html

• The List of Top 10 Lists in Data Science">The List of Top 10 Lists in Data Science

  The list of Top 10 lists that Data Scientists -- from enthusiasts to those who want to jump start a career -- must know to smoothly navigate a path through this field.

  https://www.kdnuggets.com/2020/08/top-10-lists-data-science.html

• Unit Test Your Data Pipeline, You Will Thank Yourself Later">Unit Test Your Data Pipeline, You Will Thank Yourself Later

  While you cannot test model output, at least you should test that inputs are correct. Compared to the time you invest in writing unit tests, good pieces of simple tests will save you much more time later, especially when working on large projects or big data.

  https://www.kdnuggets.com/2020/08/unit-test-data-pipeline-thank-yourself-later.html

• 10 Use Cases for Privacy-Preserving Synthetic Data

  This article presents 10 use-cases for synthetic data, showing how enterprises today can use this artificially generated information to train machine learning models or share data externally without violating individuals' privacy.

  https://www.kdnuggets.com/2020/08/10-use-cases-privacy-preserving-synthetic-data.html

• Fuzzy Joins in Python with d6tjoin

  Combining different data sources is a time suck! d6tjoin is a python library that lets you join pandas dataframes quickly and efficiently.

  https://www.kdnuggets.com/2020/07/fuzzy-joins-python-d6tjoin.html

• Building a Content-Based Book Recommendation Engine

  In this blog, we will see how we can build a simple content-based recommender system using Goodreads data.

  https://www.kdnuggets.com/2020/07/building-content-based-book-recommendation-engine.html

• Clustering Uber Rideshare Data

  This blog discusses clustering the Uber ridesharing dataset, with a focus on interpretation and understanding the concepts in the real world.

  https://www.kdnuggets.com/2020/07/clustering-rideshare-data-uber.html

• 5 Things You Don’t Know About PyCaret

  In comparison with the other open source machine learning libraries, PyCaret is an alternate low-code library that can be used to replace hundreds of lines of code with a few words only.

  https://www.kdnuggets.com/2020/07/5-things-pycaret.html

• Free Economics & Finance Courses for Data Scientists

  Here is a selection of courses for those interested in diversifying their domain knowledge into the related realms of economics and finance, with the goal of being able to apply your data science skills to these domains.

  https://www.kdnuggets.com/2020/06/free-economics-finance-courses-data-scientists.html

• Easy Speech-to-Text with Python">Easy Speech-to-Text with Python

  In this blog, I am demonstrating how to convert speech to text using Python. This can be done with the help of the “Speech Recognition” API and “PyAudio” library.

  https://www.kdnuggets.com/2020/06/easy-speech-text-python.html

• Easy Text-to-Speech with Python

  Python comes with a lot of handy and easily accessible libraries and we’re going to look at how we can deliver text-to-speech with Python in this article.

  https://www.kdnuggets.com/2020/05/easy-text-speech-python.html

• Text Mining in Python: Steps and Examples

  The majority of data exists in the textual form which is a highly unstructured format. In order to produce meaningful insights from the text data then we need to follow a method called Text Analysis.

  https://www.kdnuggets.com/2020/05/text-mining-python-steps-examples.html

• Explaining “Blackbox” Machine Learning Models: Practical Application of SHAP

  Train a "blackbox" GBM model on a real dataset and make it explainable with SHAP.

  https://www.kdnuggets.com/2020/05/explaining-blackbox-machine-learning-models-practical-application-shap.html

• Five Cool Python Libraries for Data Science">Five Cool Python Libraries for Data Science

  Check out these 5 cool Python libraries that the author has come across during an NLP project, and which have made their life easier.

  https://www.kdnuggets.com/2020/04/five-cool-python-libraries-data-science.html

• How Bad Data is Affecting Your Organization’s Operational Efficiency

  Despite recognizing the importance of data quality, many companies still fail to implement a data quality framework that could protect them from making costly mistakes. Poor data does not just cause revenue loss – it’s the reason your company could lose employees, customers and reputation!

  https://www.kdnuggets.com/2020/03/bad-data-affecting-organizations-operational-efficiency.html

• AI and Machine Learning In Our Every Day Life

  The curiosity and buzz around the most talked-about technology -- Artificial Intelligence -- have experts and technophiles busy decoding its exciting future applications. Of course, the use of AI and machine learning is already pervasive in our daily lives, as we review many of these popular features in this article.

  https://www.kdnuggets.com/2020/02/ai-machine-learning-everyday-life.html

• Classify A Rare Event Using 5 Machine Learning Algorithms

  Which algorithm works best for unbalanced data? Are there any tradeoffs?

  https://www.kdnuggets.com/2020/01/classify-rare-event-machine-learning-algorithms.html

• Beginner’s Guide to K-Nearest Neighbors in R: from Zero to Hero

  This post presents a pipeline of building a KNN model in R with various measurement metrics.

  https://www.kdnuggets.com/2020/01/beginners-guide-nearest-neighbors-r.html

• Market Basket Analysis: A Tutorial

  This article is about Market Basket Analysis & the Apriori algorithm that works behind it.

  https://www.kdnuggets.com/2019/12/market-basket-analysis.html

• How Data Analytics Can Assist in Fraud Detection

  A primary advantage of data analytics tools is that they can handle massive quantities of information at once. These solutions typically learn what's normal within a collection of information and how to spot anomalies.

  https://www.kdnuggets.com/2019/11/data-analytics-assist-fraud-detection.html

• Orchestrating Dynamic Reports in Python and R with Rmd Files

  Do you want to extract csv files with Python and visualize them in R? How does preparing everything in R and make conclusions with Python sound? Both are possible if you know the right libraries and techniques. Here, we’ll walk through a use-case using both languages in one analysis

  https://www.kdnuggets.com/2019/11/orchestrating-dynamic-reports-python-r-rmd-files.html

• Anomaly Detection, A Key Task for AI and Machine Learning, Explained

  One way to process data faster and more efficiently is to detect abnormal events, changes or shifts in datasets. Anomaly detection refers to identification of items or events that do not conform to an expected pattern or to other items in a dataset that are usually undetectable by a human expert.

  https://www.kdnuggets.com/2019/10/anomaly-detection-explained.html

• How AI will transform healthcare (and can it fix the US healthcare system?)">How AI will transform healthcare (and can it fix the US healthcare system?)

  This thorough review focuses on the impact of AI, 5G, and edge computing on the healthcare sector in the 2020s as well as a look at quantum computing's potential impact on AI, healthcare, and financial services.

  https://www.kdnuggets.com/2019/09/ai-transform-healthcare.html

• Natural Language in Python using spaCy: An Introduction

  This article provides a brief introduction to working with natural language (sometimes called “text analytics”) in Python using spaCy and related libraries.

  https://www.kdnuggets.com/2019/09/natural-language-python-using-spacy-introduction.html

• 5 Step Guide to Scalable Deep Learning Pipelines with d6tflow

  How to turn a typical pytorch script into a scalable d6tflow DAG for faster research & development.

  https://www.kdnuggets.com/2019/09/5-step-guide-scalable-deep-learning-pipelines-d6tflow.html

• Can we trust AutoML to go on full autopilot?

  We put an AutoML tool to the test on a real-world problem, and the results are surprising. Even with automatic machine learning, you still need expert data scientists.

  https://www.kdnuggets.com/2019/07/automl-full-autopilot.html

• Top 10 Best Podcasts on AI, Analytics, Data Science, Machine Learning">Top 10 Best Podcasts on AI, Analytics, Data Science, Machine Learning

  Check out our latest Top 10 Most Popular Data Science and Machine Learning podcasts available on iTunes. Stay up to date in the field with these recent episodes and join in with the current data conversations.

  https://www.kdnuggets.com/2019/07/best-podcasts-ai-analytics-data-science-machine-learning.html

• Is SQL needed to be a data scientist?

  As long as there is ‘data’ in data scientist, Structured Query Language (or see-quel as we call it) will remain an important part of it. In this blog, let us explore data science and its relationship with SQL.

  https://www.kdnuggets.com/2019/07/sql-needed-data-scientist.html

• The title CDO started out as a joke

  How did the role of Chief Data Officer come to drive data literacy at companies around the world? Find out how it all began in this interview with the first who held the title at Yahoo!

  https://www.kdnuggets.com/2019/07/title-cdo-started-as-joke.html

• Top 10 Statistics Mistakes Made by Data Scientists">Top 10 Statistics Mistakes Made by Data Scientists

  The following are some of the most common statistics mistakes made by data scientists. Check this list often to make sure you are not making any of these while applying statistics to data science.

  https://www.kdnuggets.com/2019/06/statistics-mistakes-data-scientists.html

• What Does a Lady Tasting Tea Have to Do with Science?

  Design of Experiments (DOE) is a statistical concept used to find the cause-and-effect relationships. Surprisingly, an experiment arising from a casual conversation about tea-drinking is one of the first examples of an experiment designed using statistical ideas.

  https://www.kdnuggets.com/2019/05/lady-tasting-tea-science.html

• “Please, explain.” Interpretability of machine learning models

  Unveiling secrets of black box models is no longer a novelty but a new business requirement and we explain why using several different use cases.

  https://www.kdnuggets.com/2019/05/interpretability-machine-learning-models.html

• How Machines Make Sense of Big Data: an Introduction to Clustering Algorithms

  We outline three different clustering algorithms - k-means clustering, hierarchical clustering and Graph Community Detection - providing an explanation on when to use each, how they work and a worked example.

  https://www.kdnuggets.com/2019/04/introduction-clustering-algorithms.html

• Top 10 Coding Mistakes Made by Data Scientists">Top 10 Coding Mistakes Made by Data Scientists

  Here is a list of 10 common mistakes that a senior data scientist — who is ranked in the top 1% on Stackoverflow for python coding and who works with a lot of (junior) data scientists — frequently sees.

  https://www.kdnuggets.com/2019/04/top-10-coding-mistakes-data-scientists.html

• 4 Reasons Why Your Machine Learning Code is Probably Bad">4 Reasons Why Your Machine Learning Code is Probably Bad

  Your current ML workflow probably chains together several functions executed linearly. Instead of linearly chaining functions, data science code is better written as a set of tasks with dependencies between them. That is your data science workflow should be a DAG.

  https://www.kdnuggets.com/2019/02/4-reasons-machine-learning-code-probably-bad.html

• Using Caret in R to Classify Term Deposit Subscriptions for a Bank

  This article uses direct marketing campaign data from a Portuguese banking institution to predict if a customer will subscribe for a term deposit. We’ll be working with R’s Caret package to achieve this.

  https://www.kdnuggets.com/2019/02/caret-r-classify-term-deposit-subscriptions-bank.html

• Building AI to Build AI: The Project That Won the NeurIPS AutoML Challenge

  This is an overview of designing a computer program capable of developing predictive models without any manual intervention that are trained & evaluated in a lifelong machine learning setting in NeurIPS 2018 AutoML3 Challenge.

  https://www.kdnuggets.com/2019/01/building-ai-to-build-ai-neurips-automl-challenge.html

• A Case For Explainable AI & Machine Learning

  In support of the explainable AI cause, we present a variety of use cases covering operational needs, regulatory compliance and public trust and social acceptance.

  https://www.kdnuggets.com/2018/12/explainable-ai-machine-learning.html

• KDnuggets Site Map

  About KDnuggets Awards and Honors for KDnuggets Companies, offering Bioinformatics products and solutions Data Science and Analytics products Consulting and Training Data Warehousing and OLAP Read more »

  https://www.kdnuggets.com/about/site-map.html

• Evaluating the Business Value of Predictive Models in Python and R

  In these blogs for R and python we explain four valuable evaluation plots to assess the business value of a predictive model. We show how you can easily create these plots and help you to explain your predictive model to non-techies.

  https://www.kdnuggets.com/2018/10/evaluating-business-value-predictive-models-modelplotpy.html

• What is Web Scraping and Why You Should Learn It?

  Introducing Octoparse - a sleek, powerful and easy-to-use software that makes web scraping from any websites achievable for most people, including non-coders.

  https://www.kdnuggets.com/2018/09/octoparse-web-scraping.html

• The Industries That Can Benefit Most From Predictive Analytics

  Predictive analytics are useful for doing all those things and more, and could increase the overall competitiveness of individual companies or entire sectors.

  https://www.kdnuggets.com/2018/07/industries-benefit-most-predictive-analytics.html

• 5 of Our Favorite Free Visualization Tools">5 of Our Favorite Free Visualization Tools

  5 key free data visualization tools that can provide flexible and effective data presentation.

  https://www.kdnuggets.com/2018/07/5-favorite-open-source-visualization-tools.html

• The Future of Artificial Intelligence: Is Your Job Under Threat?

  This article examines the rapid growth of artificial intelligence: how we got to this point, the future AI job market and what can be done.

  https://www.kdnuggets.com/2018/06/future-ai-job-under-threat.html

• Blockchain Explained in 7 Python Functions">Blockchain Explained in 7 Python Functions

  It wasn’t until I wrote my own simple Blockchain, that I truly understood what it is and the potential applications for it. So without further ado, lets set up our 7 functions!

  https://www.kdnuggets.com/2018/04/blockchain-explained-7-python-functions.html

• Top 10 Technology Trends of 2018">Top 10 Technology Trends of 2018

  In this article, we will focus on the modern trends that took off well on the market by the end of 2017 and discuss the major breakthroughs expected in 2018.

  https://www.kdnuggets.com/2018/04/top-10-technology-trends-2018.html

• New Book: Credit risk analytics, The R Companion

  Credit risk analytics in R will enable you to build credit risk models from start to finish, with access to real credit data on accompanying website, you will master a wide range of applications.

  https://www.kdnuggets.com/2018/03/baesens-book-credit-risk-analytics-r.html

• Blockchains and APIs

  Major technological advances are providing opportunities for new business models, based on blockchain, which will see an increase in the number of connected devices in our day-to-day lives.

  https://www.kdnuggets.com/2018/03/blockchains-apis.html

• Time Series for Dummies – The 3 Step Process">Time Series for Dummies – The 3 Step Process

  Time series forecasting is an easy to use, low-cost solution that can provide powerful insights. This post will walk through introduction to three fundamental steps of building a quality model.

  https://www.kdnuggets.com/2018/03/time-series-dummies-3-step-process.html

• Data Structures Related to Machine Learning Algorithms">Data Structures Related to Machine Learning Algorithms

  If you want to solve some real-world problems and design a cool product or algorithm, then having machine learning skills is not enough. You would need good working knowledge of data structures.

  https://www.kdnuggets.com/2018/01/data-structures-related-machine-learning-algorithms.html

• Can I Become a Data Scientist: Research into 1,001 Data Scientist Profiles">Can I Become a Data Scientist: Research into 1,001 Data Scientist Profiles

  Results from a survey include: the average data scientist is a male, with median experience on the job is 2 years. He uses R, Python, and SQL. Read for more details.

  https://www.kdnuggets.com/2017/12/research-1001-data-scientist-profiles.html

• Machine Learning & Artificial Intelligence: Main Developments in 2017 and Key Trends in 2018">Machine Learning & Artificial Intelligence: Main Developments in 2017 and Key Trends in 2018

  As we bid farewell to one year and look to ring in another, KDnuggets has solicited opinions from numerous Machine Learning and AI experts as to the most important developments of 2017 and their 2018 key trend predictions.

  https://www.kdnuggets.com/2017/12/machine-learning-ai-main-developments-2017-key-trends-2018.html

• Data Science, Machine Learning: Main Developments in 2017 and Key Trends in 2018">Data Science, Machine Learning: Main Developments in 2017 and Key Trends in 2018

  The leading experts in the field on the main Data Science, Machine Learning, Predictive Analytics developments in 2017 and key trends in 2018.

  https://www.kdnuggets.com/2017/12/data-science-machine-learning-main-developments-trends.html

• The Qualitative Side of Quantitative Research

  Kevin and Koen may buy the same brand for the same reasons. On the other hand, they may buy the same brand for different reasons, or buy different brands for the same reasons, or even different brands for different reasons. The brands they purchase and the reasons why may vary by occasion, too.

  https://www.kdnuggets.com/2017/11/qualitative-side-quantitative-research.html

• Introduction to Blockchains & What It Means to Big Data">Introduction to Blockchains & What It Means to Big Data

  Perhaps most significant development in IT over the past few years, blockchain has the potential to change the way that the world approaches big data, with enhanced security and data quality.

  https://www.kdnuggets.com/2017/09/introduction-blockchain-big-data.html

• Python Data Preparation Case Files: Removing Instances & Basic Imputation

  This is the first of 3 posts to cover imputing missing values in Python using Pandas. The slowest-moving of the series (out of necessity), this first installment lays out the task and data at the risk of boring you. The next 2 posts cover group- and regression-based imputation.

  https://www.kdnuggets.com/2017/09/python-data-preparation-case-files-basic-imputation.html

• New-Age Machine Learning Algorithms in Retail Lending">New-Age Machine Learning Algorithms in Retail Lending

  We review the application of new age Machine Learning algorithms for better Customer Analytics in Lending and Credit Risk Assessment.

  https://www.kdnuggets.com/2017/09/machine-learning-algorithms-lending.html

• Introduction to Neural Networks, Advantages and Applications">Introduction to Neural Networks, Advantages and Applications

  Artificial Neural Network (ANN) algorithm mimic the human brain to process information. Here we explain how human brain and ANN works.

  https://www.kdnuggets.com/2017/07/introduction-neural-networks-advantages-applications.html

• Spotlight on the Remarkable Potential of AI in KYC (Know Your Customer)

  Most people would have heard of the headline-making tremendous achievements in artificial intelligence (AI): Systems defeating world champions in board games like GO and winning quiz shows. These are small realizations of AI, but there is a silent revolution taking place in other areas, including Regulatory Compliance in Financial Services.

  https://www.kdnuggets.com/2017/07/spotlight-remarkable-potential-ai-kyc.html

• The Analytics of Emotion and Depression

  Analytics can be used to provide a boost to the cure of depression. How analytics is being adopted by companies like Microsoft, Facebook to handle and detect vulnerable targets of depression.

  https://www.kdnuggets.com/2017/04/analytics-emotion-depression.html

• How to think like a data scientist to become one

  The author went from securities analyst to Head of Data Science at Amazon. He describes what he learned in his journey and gives 4 useful rules based on his experience.

  https://www.kdnuggets.com/2017/03/think-like-data-scientist-become-one.html

• KDnuggets Consulting – expert advice on Business Analytics, Data Mining, and Data Science

  Gregory Piatetsky-Shapiro Experience Education Presentations & Tutorials Recent Publications Contact: [my first name] at kdnuggets.com, with a brief description of the issues. Gregory Piatetsky-Shapiro, Ph.D., Read more »

  https://www.kdnuggets.com/data-mining-consulting.html

• Machine Learning vs Statistics">Machine Learning vs Statistics

  Machine learning is all about predictions, supervised learning, and unsupervised learning, while statistics is about sample, population, and hypotheses. But are they actually that different?

  https://www.kdnuggets.com/2016/11/machine-learning-vs-statistics.html