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Found 6292 documents, 6021 searched:

• Top 5 Bookmarks Every Data Analyst Should Have

  Check out these online tools to save you time & effort.

  https://www.kdnuggets.com/2022/09/top-5-bookmarks-every-data-analyst.html

• Simplifying Decision Tree Interpretability with Python & Scikit-learn

  This post will look at a few different ways of attempting to simplify decision tree representation and, ultimately, interpretability. All code is in Python, with Scikit-learn being used for the decision tree modeling.

  https://www.kdnuggets.com/2017/05/simplifying-decision-tree-interpretation-decision-rules-python.html

• How Data Science Fuels Fraud Prevention

  By themselves, these data points will probably not provide much insight into a single customer. However, a company that has some or all of this information is well-positioned to have a strong idea of how legitimate its visitors are.

  https://www.kdnuggets.com/2022/09/data-science-fuels-fraud-prevention.html

• An Intuitive Explanation of Collaborative Filtering

  The post introduces one of the most popular recommendation algorithms, i.e., collaborative filtering. It focuses on building an intuitive understanding of the algorithm illustrated with the help of an example.

  https://www.kdnuggets.com/2022/09/intuitive-explanation-collaborative-filtering.html

• Free SQL and Database Course

  Get up to speed on SQL and relational databases with this free video course.

  https://www.kdnuggets.com/2022/09/free-sql-database-course.html

• Top Open Source Large Language Models

  In this article, we will discuss the importance of large language models and suggest some of the top open source models and the NLP tasks they can be used for.

  https://www.kdnuggets.com/2022/09/john-snow-top-open-source-large-language-models.html

• 7 Steps to Mastering Python for Data Science

  Here’s how you can learn to code in Python from scratch in 7 easy steps.

  https://www.kdnuggets.com/2022/06/7-steps-mastering-python-data-science.html

• Why Organizations Need Data Warehouses

  So where can you store, harness and collect findings in your data - in one place? What is the right tool for this? Data Warehouses

  https://www.kdnuggets.com/2022/09/organizations-need-data-warehouses.html

• KDnuggets News, September 14: Free Python for Data Science Course • Everything You’ve Ever Wanted to Know About Machine Learning

  Free Python for Data Science Course • Everything You’ve Ever Wanted to Know About Machine Learning • Progress Bars in Python with tqdm for Fun and Profit • 7 Tips for Python Beginners • 7 Data Analytics Interview Questions & Answers

  https://www.kdnuggets.com/2022/n36.html

• KDnuggets Applied Data Science Survey

  We want to know where you applied data science in the past 12 months.

  https://www.kdnuggets.com/2022/09/applied-data-science-survey.html

• ModelOps: What you need to know to get certified

  Find out why ModelOps is in-demand and how SAS can help you propel in this growing area. 

  https://www.kdnuggets.com/2022/09/sas-modelops-need-know-get-certified.html

• Find a Picture in an Image Without Marking it Up

  Let's take a closer look at our algorithm so that you can test it with a notebook in Google Colaboratory and even implement it in your project.

  https://www.kdnuggets.com/2022/09/find-picture-image-without-marking.html

• Top Posts August 29 – September 11: Free Python for Data Science Course

  Free Python for Data Science Course • How to Select Rows and Columns in Pandas Using [ ], .loc, iloc, .at and .iat • Everything You've Ever Wanted to Know About Machine Learning • 7 Tips for Python Beginners • 5 Tricky SQL Queries Solved

  https://www.kdnuggets.com/2022/09/top-posts-week-0829-0911.html

• Removing Outliers Using Standard Deviation in Python

  Standard Deviation is one of the most underrated statistical tools out there. It’s an extremely useful metric that most people know how to calculate but very few know how to use effectively.

  https://www.kdnuggets.com/2017/02/removing-outliers-standard-deviation-python.html

• 7 Data Analytics Interview Questions & Answers

  Most asked non-technical, operational, and SQL interview questions for data analytics jobs.

  https://www.kdnuggets.com/2022/09/7-data-analytics-interview-questions-answers.html

• Everything You’ve Ever Wanted to Know About Machine Learning

  Putting the fun in fundamentals! A collection of short videos to amuse beginners and experts alike.

  https://www.kdnuggets.com/2022/09/everything-youve-ever-wanted-to-know-about-machine-learning.html

• All About Collections in Python

  In this tutorial, we would be exploring different types of containers implemented by the collections module.

  https://www.kdnuggets.com/2022/09/collections-python.html

• How To Tackle 3 Common Machine Learning Challenges

  As you begin developing your ML models, here are the common challenges you might encounter during your project.

  https://www.kdnuggets.com/2022/09/comet-tackle-3-common-machine-learning-challenges.html

• Everything You Need to Know About Data Lakehouses

  Learn everything you need to know about data lakehouses.

  https://www.kdnuggets.com/2022/09/everything-need-know-data-lakehouses.html

• 7 Things You Didn’t Know You Could do with a Low Code Tool

  Surprisingly easy solutions for complex data problems.

  https://www.kdnuggets.com/2022/09/7-things-didnt-know-could-low-code-tool.html

• Join Data Literacy Month 2022

  This September, DataCamp are dedicating an entire month to supporting individuals and organizations to drive data literacy as part of their mission to democratize data skills for everyone.

  https://www.kdnuggets.com/2022/09/datacamp-join-data-literacy-month-2022.html

• Machine Learning Algorithms – What, Why, and How?

  This post explains why and when you need machine learning and concludes by listing the key considerations for choosing the correct machine learning algorithm.

  https://www.kdnuggets.com/2022/09/machine-learning-algorithms.html

• Convert Text Documents to a TF-IDF Matrix with tfidfvectorizer

  Convert text documents to vectors using TF-IDF vectorizer for topic extraction, clustering, and classification.

  https://www.kdnuggets.com/2022/09/convert-text-documents-tfidf-matrix-tfidfvectorizer.html

• Choosing the Right Clustering Algorithm for Your Dataset

  Applying a clustering algorithm is much easier than selecting the best one. Each type offers pros and cons that must be considered if you’re striving for a tidy cluster structure.

  https://www.kdnuggets.com/2019/10/right-clustering-algorithm.html

• How to build a model to find the most impactful paths in user journeys

  In this how-to, we’ll build a model to uncover which paths in user journeys have the biggest impact on product goals (e.g. conversion). You can use it to improve products or optimize marketing campaigns, or as a base for deeper user behavior analyses.

  https://www.kdnuggets.com/2022/09/objectiv-build-model-impactful-paths-user-journeys.html

• 8 Innovative BERT Knowledge Distillation Papers That Have Changed The Landscape of NLP

  All of the papers present a particular point of view of findings in the BERT utilization.

  https://www.kdnuggets.com/2022/09/eight-innovative-bert-knowledge-distillation-papers-changed-nlp-landscape.html

• 24 A/B Testing Interview Questions in Data Science Interviews and How to Crack Them

  Here’s everything you need to know about A/B testing interview questions in data science interviews.

  https://www.kdnuggets.com/2022/09/24-ab-testing-interview-questions-data-science-interviews-crack.html

• Visualizing Your Confusion Matrix in Scikit-learn

  Defining model evaluation metrics is crucial in ensuring that the model performs precisely for the purpose it is built. Confusion Matrix is one of the most popular and effective tools to evaluate the performance of the trained ML model. In this post, you will learn how to visualize the confusion matrix and interpret its output.

  https://www.kdnuggets.com/2022/09/visualizing-confusion-matrix-scikitlearn.html

• SQL vs NoSQL: 7 Key Takeaways

  People assume that NoSQL is a counterpart to SQL. Instead, it’s a different type of database designed for use-cases where SQL is not ideal. The differences between the two are many, although some are so crucial that they define both databases at their cores.

  https://www.kdnuggets.com/2020/12/sql-vs-nosql-7-key-takeaways.html

• 7 Tips for Python Beginners

  Learn useful tips to start your career as a Python developer.

  https://www.kdnuggets.com/2022/09/7-tips-python-beginners.html

• Free Python for Data Science Course

  Ready to learn how to use Python for data science? This free course has got you covered!

  https://www.kdnuggets.com/2022/09/free-python-data-science-course.html

• What’s New On KDnuggets?

  KDnuggets has been up to some things over the past several months. Check in quick to make sure you haven't missed anything.

  https://www.kdnuggets.com/2022/09/whats-new-kdnuggets.html

• Combining Pandas DataFrames Made Simple

  For this tutorial, we will work through examples to understand how different mehtods for combining Pandas DataFrames work.

  https://www.kdnuggets.com/2022/09/combining-pandas-dataframes-made-simple.html

• Decision Tree Pruning: The Hows and Whys

  Decision trees are a machine learning algorithm that is susceptible to overfitting. One of the techniques you can use to reduce overfitting in decision trees is pruning.

  https://www.kdnuggets.com/2022/09/decision-tree-pruning-hows-whys.html

• How to Select Rows and Columns in Pandas Using [ ], .loc, iloc, .at and .iat

  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.

  https://www.kdnuggets.com/2019/06/select-rows-columns-pandas.html

• Progress Bars in Python with tqdm for Fun and Profit

  Add progress bar to the Python functions, Jupyter Notebook, and pandas dataframe.

  https://www.kdnuggets.com/2022/09/progress-bars-python-tqdm-fun-profit.html

• KDnuggets News, August 31: The Complete Data Science Study Roadmap • 7 Techniques to Handle Imbalanced Data

  The Complete Data Science Study Roadmap • 7 Techniques to Handle Imbalanced Data • 3 Ways to Append Rows to Pandas DataFrames • The Bias-Variance Trade-off • How to Package and Distribute Machine Learning Models with MLFlow

  https://www.kdnuggets.com/2022/n35.html

• The Difference Between Training and Testing Data in Machine Learning

  When building a predictive model, the quality of the results depends on the data you use. In order to do so, you need to understand the difference between training and testing data in machine learning.

  https://www.kdnuggets.com/2022/08/difference-training-testing-data-machine-learning.html

• Machine Learning Metadata Store

  In this article, we will learn about metadata stores, the need for them, their components, and metadata store management.

  https://www.kdnuggets.com/2022/08/machine-learning-metadata-store.html

• Machine Learning in the Enterprise: Use Cases & Challenges

  This article provides insights into how leading data scientists are embracing machine learning in their organizations and covers some of the major ML challenges and trends in the enterprise.

  https://www.kdnuggets.com/2022/08/dss-machine-learning-enterprise-cases-challenges.html

• Data Governance and Observability, Explained

  Let’s dive in and understand the ins and outs of data observability and data governance - the two keys to a more robust data foundation.

  https://www.kdnuggets.com/2022/08/data-governance-observability-explained.html

• The Benefits of Natural Language AI for Content Creators

  In this article, we will discuss the benefits of natural language AI for content creators, highlighting the key reasons why you should consider using it to improve your content output.

  https://www.kdnuggets.com/2022/08/benefits-natural-language-ai-content-creators.html

• Top Posts August 22-28: Free Python Project Coding Course

  Free Python Project Coding Course • 5 Tricky SQL Queries Solved • Decision Tree Algorithm, Explained • Free AI for Beginners Course • The Complete Collection of Data Science Projects & Part 2

  https://www.kdnuggets.com/2022/08/top-posts-week-0822-0828.html

• 3 Ways to Append Rows to Pandas DataFrames

  Learn a simple way to append rows in the form of arrays, dictionaries, series, and dataframes to another dataframe.

  https://www.kdnuggets.com/2022/08/3-ways-append-rows-pandas-dataframes.html

• Build a Reproducible and Maintainable Data Science Project: A Free Online Book

  This free online book is a fantastic resource on how to structure, manage, and maintain your real-world data science projects.

  https://www.kdnuggets.com/2022/08/free-book-build-reproducible-maintainable-data-science-project.html

• A Complete Guide To Decision Tree Software

  Decision tree models are used to classify information into meaningful sequential results. Find out everything else you need to know here.

  https://www.kdnuggets.com/2022/08/complete-guide-decision-tree-software.html

• Machine Learning is Not Like Your Brain Part Seven: What Neurons are Good At

  Thus far, this series has focused on things that Machine Learning does or needs which biological neurons simply can’t do. This article turns the tables and discusses a few things that neurons are particularly good at.

  https://www.kdnuggets.com/2022/08/machine-learning-like-brain-part-seven-neurons-good.html

• Put your deep learning skills with R into action!

  Sponsored Post     Deep learning has become essential knowledge for data scientists, researchers, and software developers. The R language APIs for Keras and TensorFlow Read more »

  https://www.kdnuggets.com/2022/08/manning-deep-learning-skills-r-action.html

• How to Better Leverage Data Science for Business Growth

  Is data science for you? And if it is, how can you use it to grow your business?

  https://www.kdnuggets.com/2022/08/better-leverage-data-science-business-growth.html

• How to Package and Distribute Machine Learning Models with MLFlow

  MLFlow is a tool to manage the end-to-end lifecycle of a Machine Learning model. Likewise, the installation and configuration of an MLFlow service is addressed and examples are added on how to generate and share projects with MLFlow.

  https://www.kdnuggets.com/2022/08/package-distribute-machine-learning-models-mlflow.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 Bias-Variance Trade-off

  Understanding how these prediction errors work and how they can be used will help you build models that are not only accurate and perform well - but also avoid overfitting and underfitting.

  https://www.kdnuggets.com/2022/08/biasvariance-tradeoff.html

• KDnuggets News, August 24: Implementing DBSCAN in Python • How to Avoid Overfitting

  Implementing DBSCAN in Python • How to Avoid Overfitting • Simplify Data Processing with Pandas Pipeline • How to Use Data Visualization to Add Impact to Your Work Reports and Presentations • The Data Quality Hierarchy of Needs

  https://www.kdnuggets.com/2022/n34.html

• Top Posts August 15-21: How to Perform Motion Detection Using Python

  How to Perform Motion Detection Using Python • The Complete Collection of Data Science Projects – Part 2 • Free AI for Beginners Course • Decision Tree Algorithm, Explained • What Does ETL Have to Do with Machine Learning?

  https://www.kdnuggets.com/2022/08/top-posts-week-0815-0821.html

• Customize Your Data Frame Column Names in Python

  This tutorial will explore four scenarios in which you can apply different transformations to all DataFrame columns.

  https://www.kdnuggets.com/2022/08/customize-data-frame-column-names-python.html

• Support Vector Machines: An Intuitive Approach

  This post focuses on building an intuition of the Support Vector Machine algorithm in a classification context and an in-depth understanding of how that graphical intuition can be mathematically represented in the form of a loss function. We will also discuss kernel tricks and a more useful variant of SVM with a soft margin.

  https://www.kdnuggets.com/2022/08/support-vector-machines-intuitive-approach.html

• The 5 Surprising Things You Can Do With R

  This article will dive into R's different uses and demonstrate what you can do with this programming language once you've learned it.

  https://www.kdnuggets.com/2022/08/5-surprising-things-r.html

• KDnuggets Top Posts for July 2022: Machine Learning Algorithms Explained in Less Than 1 Minute Each

  Machine Learning Algorithms Explained in Less Than 1 Minute Each • Free Python Automation Course • Free Python Crash Course • The 5 Hardest Things to Do in SQL • 16 Essential DVC Commands for Data Science • 12 Essential VSCode Extensions for Data Science • Parallel Processing Large • File in Python • Linear Algebra for Data Science

  https://www.kdnuggets.com/2022/08/top-posts-july-2022.html

• Simplify Data Processing with Pandas Pipeline

  Write a single line of code to clean and process the data for analytics and machine learning tasks.

  https://www.kdnuggets.com/2022/08/simplify-data-processing-pandas-pipeline.html

• Tuning Random Forest Hyperparameters

  Hyperparameter tuning is important for algorithms. It improves their overall performance of a machine learning model and is set before the learning process and happens outside of the model.

  https://www.kdnuggets.com/2022/08/tuning-random-forest-hyperparameters.html

• Free Python Project Coding Course

  Learn Python by doing Python. Check out this free project-based course to quickly learn how to program in the high-demand language.

  https://www.kdnuggets.com/2022/08/free-python-project-coding-course.html

• Last call: Stefan Krawcyzk’s ‘Mastering MLOps’ Live Cohort

  This is your last chance to sign up for Stefan Krawczyk's exclusive live cohort, starting August 22. We already have students enrolled from Apple, Amazon, Spotify, Nubank, Workfusion, Glassdoor, ServiceNow, and more.

  https://www.kdnuggets.com/2022/08/sphere-last-call-stefan-krawcyzk-mastering-mlops.html

• How to Use Data Visualization to Add Impact to Your Work Reports and Presentations

  For anyone whose work involves presenting data, understanding the art and science of data visualization — and its emphasis on storytelling — can make or break your ability to communicate key insights.

  https://www.kdnuggets.com/2022/08/data-visualization-add-impact-work-reports-presentations.html

• 5 Tricky SQL Queries Solved

  Explaining the approach to solving a few complex SQL queries.

  https://www.kdnuggets.com/2020/11/5-tricky-sql-queries-solved.html

• Type I and Type II Errors: What’s the Difference?

  Looking to sort out the difference between Type I and Type II errors? Read on for more.

  https://www.kdnuggets.com/2022/08/type-type-ii-errors-difference.html

• How Do Data Scientists and Data Engineers Work Together?

  If you’re considering a career in data science, it’s important to understand how these two fields differ, and which one might be more appropriate for someone with your skills and interests.

  https://www.kdnuggets.com/2022/08/data-scientists-data-engineers-work-together.html

• The Data Quality Hierarchy of Needs

  Just as Maslow identified a hierarchy of needs for people, data teams have a hierarchy of needs, beginning with data freshness; including volumes, schemas, and values; and culminating with lineage.

  https://www.kdnuggets.com/2022/08/data-quality-hierarchy-needs.html

• How CoRise Helped Ben Wilson Land a New Job as a Analytics Engineer (and a Side Gig in Doodling)

  In this practical modern data stack course, you will implement a dbt project on a data warehouse from scratch and with a lot of support along the way!

  https://www.kdnuggets.com/2022/08/corise-land-new-job-analytics-engineer.html

• Implementing DBSCAN in Python

  Density-based clustering algorithm explained with scikit-learn code example.

  https://www.kdnuggets.com/2022/08/implementing-dbscan-python.html

• How to Avoid Overfitting

  Overfitting is when a statistical model fits exactly against its training data. This leads to the model failing to predict future observations accurately.

  https://www.kdnuggets.com/2022/08/avoid-overfitting.html

• KDnuggets News, August 17: How to Perform Motion Detection Using Python • The Complete Collection of Data Science Projects

  How to Perform Motion Detection Using Python • The Complete Collection of Data Science Projects - Part 2 • What Does ETL Have to Do with Machine Learning? • Data Transformation: Standardization vs Normalization • The Evolution From Artificial Intelligence to Machine Learning to Data Science

  https://www.kdnuggets.com/2022/n33.html

• Is There a Way to Bridge the MLOps Tools Gap?

  Converting Jupyter notebooks to a well-designed software system is a mandatory step in every ML project. But there is a notable lack of tooling to assist developers with such translation, beyond the basic nbconvert utility.

  https://www.kdnuggets.com/2022/08/way-bridge-mlops-tools-gap.html

• Machine Learning Over Encrypted Data

  This blog outlines a solution to the Kaggle Titanic challenge that employs Privacy-Preserving Machine Learning (PPML) using the Concrete-ML open-source toolkit.

  https://www.kdnuggets.com/2022/08/machine-learning-encrypted-data.html

• Why is Data Management so Important to Data Science?

  High data availability may help power digital transformation, but data management systems are needed to keep that data organized and make it accessible. Read this article to see why data management is important to data science.

  https://www.kdnuggets.com/2022/08/data-management-important-data-science.html

• Top Posts August 8-14: Free AI for Beginners Course

  Free AI for Beginners Course • How to Perform Motion Detection Using Python • 3 Free Statistics Courses for Data Science • The 5 Hardest Things to Do in SQL • Decision Tree Algorithm, Explained

  https://www.kdnuggets.com/2022/08/top-posts-week-0808-0814.html

• What Does ETL Have to Do with Machine Learning?

  ETL during the process of producing effective machine learning algorithms is found at the base - the foundation. Let’s go through the steps on how ETL is important to machine learning.

  https://www.kdnuggets.com/2022/08/etl-machine-learning.html

• The Complete Collection of Data Science Projects – Part 2

  The second part covers the list of Machine Learning, Deep Learning, Computer Vision, Natural Language Processing, Data Engineering, and MLOps.

  https://www.kdnuggets.com/2022/08/complete-collection-data-science-projects-part-2.html

• How to Perform Motion Detection Using Python

  In this article, we will specifically take a look at motion detection using a webcam of a laptop or computer and will create a code script to work on our computer and see its real-time example.

  https://www.kdnuggets.com/2022/08/perform-motion-detection-python.html

• The Importance of Experiment Design in Data Science

  Do you feel overwhelmed by the sheer number of ideas that you could try while building a machine learning pipeline? You can not take the liberty of trying all possible ways to arrive at a solution - hence we discuss the importance of experiment design in data science projects.

  https://www.kdnuggets.com/2022/08/importance-experiment-design-data-science.html

• Data Transformation: Standardization vs Normalization

  Increasing accuracy in your models is often obtained through the first steps of data transformations. This guide explains the difference between the key feature scaling methods of standardization and normalization, and demonstrates when and how to apply each approach.

  https://www.kdnuggets.com/2020/04/data-transformation-standardization-normalization.html

• How to land an ML job: Advice from engineers at Meta, Google Brain, and SAP

  Check out this video, summary and transcript of a discussion between co:rise co-founder Jake Samuelson and three outstanding ML engineers — Kaushik Rangadurai, Shalvi Mahajan, and Frank Chen — to hear their advice on landing a job in machine learning.

  https://www.kdnuggets.com/2022/08/corise-land-ml-job-advice-engineers-meta-google-brain-sap.html

• 5 Key Data Science Trends & Analytics Trends

  Let’s have a look at some of the key tech trends on the horizon right now.

  https://www.kdnuggets.com/2022/08/5-key-data-science-trends-analytics-trends.html

• AI for Ukraine is a new educational project from AI HOUSE to support the Ukrainian tech community

  “AI for Ukraine” is a series of workshops and lectures held by international artificial intelligence experts to support the development of Ukraine’s tech community during the war. This is a non-commercial educational project by AI HOUSE – a company focused on building the AI/ML community in Ukraine and is part of the Roosh tech ecosystem.

  https://www.kdnuggets.com/2022/08/ai-house-ai-ukraine-new-educational-project-support-ukrainian-tech-community.html

• Tuning XGBoost Hyperparameters

  Hyperparameter tuning is about finding a set of optimal hyperparameter values which maximizes the model's performance, minimizes loss, and produces better outputs.

  https://www.kdnuggets.com/2022/08/tuning-xgboost-hyperparameters.html

• September 26-30: SIAM Conference on Mathematics of Data Science (Hybrid)

  Join researchers, practitioners, educators, and students from around the world working in industry, government, laboratories, and academia for this thought-provoking conference.

  https://www.kdnuggets.com/2022/08/siam-conference-mathematics-data-science-hybrid.html

• The Difference Between L1 and L2 Regularization

  Two types of regularized regression models are discussed here: Ridge Regression (L2 Regularization), and Lasso Regression (L1 Regularization)

  https://www.kdnuggets.com/2022/08/difference-l1-l2-regularization.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

• 3 Benefits to A/B Testing (+ Where to Get Started)

  Let’s look at 3 concrete benefits that demonstrate why A/B testing is worth your time and effort. Then learn more about Ronny’s upcoming course, "Accelerating Innovation with A/B Testing."

  https://www.kdnuggets.com/2022/08/sphere-3-benefits-ab-testing-get-started.html

• 6 Ways Businesses Can Benefit From Machine Learning

  Machine learning is gaining popularity rapidly in the business world. Discover the ways that your business can benefit from machine learning.

  https://www.kdnuggets.com/2022/08/6-ways-businesses-benefit-machine-learning.html

• 3 Free Statistics Courses for Data Science

  Statistics is one of the most in-demand data science skills. Master it for free with these online courses.

  https://www.kdnuggets.com/2022/08/3-free-statistics-courses-data-science.html

• Top Posts August 1-7: Most In-demand Artificial Intelligence Skills To Learn In 2022

  Most In-demand Artificial Intelligence Skills To Learn In 2022 • The 5 Hardest Things to Do in SQL • 10 Most Used Tableau Functions • Decision Trees vs Random Forests, Explained • Decision Tree Algorithm, Explained

  https://www.kdnuggets.com/2022/08/top-posts-week-0801-0807.html

• Best Instagram Accounts to Follow for Data Science, Machine Learning & AI

  I have put this blog together to help you figure out what Instagram accounts you should follow to get the best Data Science, Machine Learning, and Artificial Intelligence content.

  https://www.kdnuggets.com/2022/08/best-instagram-accounts-follow-data-science-machine-learning-ai.html

• The Complete Collection of Data Science Projects – Part 1

  The first part covers the list of Programming, Web scraping, Data Analytics, SQL, Business Intelligence, and Time Series projects.

  https://www.kdnuggets.com/2022/08/complete-collection-data-science-projects-part-1.html

• Free AI for Beginners Course

  Microsoft has put together an AI course for beginners, consisting of a 12 week, 24 lesson curriculum, available for free to all.

  https://www.kdnuggets.com/2022/08/free-ai-beginners-course.html

• Machine Learning Is Not Like Your Brain Part 6: The Importance of Precise Synapse Weights and the Ability to Set Them Quickly

  In Part Six, I’ll show how limitations in synapses are even more of a problem. Precise synapse weights and the ability to set them quickly to a specific value are crucial to ML and biological neurons offer neither.

  https://www.kdnuggets.com/2022/08/machine-learning-like-brain-part-6-importance-precise-synapse-weights-ability-set-quickly.html

• Where Does Data Come From?

  In this article, we will go over the top five ways to collect or receive data, whether to help optimize an AI-driven machine or simply forecast future consumer demand.

  https://www.kdnuggets.com/2022/08/data-come.html

• Why Emily Ekdahl chose co:rise to level up her job performance as a machine learning engineer

  Find out what one of the first learners to complete the co:rise Machine Learning Foundations track said about her experience in the track and what she’s tackling next when she recently talked to Julia Stiglitz, co:rise co-founder and CEO.

  https://www.kdnuggets.com/2022/08/corise-emily-ekdahl-chose-corise-level-job-performance-machine-learning-engineer.html

• Most In-demand Artificial Intelligence Skills To Learn In 2022

  Artificial Intelligence (AI) is the process of programming a computer that can reason and learn like a human being and make decisions for itself.

  https://www.kdnuggets.com/2022/08/indemand-artificial-intelligence-skills-learn-2022.html

• How to Deal with Categorical Data for Machine Learning

  Check out this guide to implementing different types of encoding for categorical data, including a cheat sheet on when to use what type.

  https://www.kdnuggets.com/2021/05/deal-with-categorical-data-machine-learning.html

• What are the Assumptions of XGBoost?

  In this article, you will learn: how boosting relates to XGBoost; the features of XGBoost; how it reduces the loss function value and overfitting.

  https://www.kdnuggets.com/2022/08/assumptions-xgboost.html

• Getting Started with SQL Cheatsheet

  Want to get started with SQL? Check out the latest cheatsheet from KDnuggets to get up to speed on the basics of one of the most popular, useful, and in-demand languages in the world of data science.

  https://www.kdnuggets.com/2022/08/getting-started-sql-cheatsheet.html

• A community developing a Hugging Face for customer data modeling

  A year ago, Objectiv started a community of 50 companies to develop a Hugging Face like open-source project for customer data modeling. They key objective: enable building data models on one team/company’s dataset, and then run them seamlessly on another.

  https://www.kdnuggets.com/2022/08/objectiv-community-developing-hugging-face-customer-data-modeling.html

• Full Stack Everything? Organizational Intersections Between Data Science, Dev & Tech

  Breakthrough value is found when teams collaborate at their intersections to come up with innovative solutions.

  https://www.kdnuggets.com/2022/08/full-stack-everything-organizational-intersections-data-science-dev-tech.html

• KDnuggets News, August 3: 10 Most Used Tableau Functions • Is Domain Knowledge Important for Machine Learning?

  10 Most Used Tableau Functions • Is Domain Knowledge Important for Machine Learning? • ETL vs ELT: Data Integration Showdown • Free MLOps Crash Course for Beginners • 90% of Today’s Code is Written to Prevent Failure, and That’s a Problem

  https://www.kdnuggets.com/2022/n31.html

• Preparing for a Data Analyst Interview

  The interview process for the job can sometimes be a bit daunting. However, with the right knowledge and preparation, you can make sure you ace the interview and land your dream job. Read this summary of DataCamp’s full article on how to prepare for a data analyst interview, presenting some of the key points. 

  https://www.kdnuggets.com/2022/08/datacamp-preparing-data-analyst-interview.html

• Trust in AI is Priceless

  Many machine learning models fail to deliver. Sadly, it’s often due to a lack of focus on data quality.

  https://www.kdnuggets.com/2022/08/trust-ai-priceless.html

• Decision Trees vs Random Forests, Explained

  A simple, non-math heavy explanation of two popular tree-based machine learning models.

  https://www.kdnuggets.com/2022/08/decision-trees-random-forests-explained.html

• ETL vs ELT: Data Integration Showdown

  Extract-Transform-Load vs Extract-Load-Transform: Data integration methods used to transfer data from one source to a data warehouse. Their aims are similar, but see how they differ.

  https://www.kdnuggets.com/2022/08/etl-elt-data-integration-showdown.html

• 10 Most Used Tableau Functions

  Learn about the most used string, number, date, logical, and aggregation Tableau functions.

  https://www.kdnuggets.com/2022/08/10-used-tableau-functions.html

• Free MLOps Crash Course for Beginners

  Interest in, and demand for, MLOps is growing exponentially. What, exactly, is it? Why is it important? Where should you turn next to learn more? Check out this crash course to find the answers to these questions and more.

  https://www.kdnuggets.com/2022/08/free-mlops-crash-course.html

• Online Training and Workshops with Nvidia

  Learn about the Nvidia Self-Paced Online Training from their Deep Learning Institute.

  https://www.kdnuggets.com/2022/07/online-training-workshops-nvidia.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

• Be prepared to manage the threat with an MS in Cybersecurity from Bay Path University

  Bay Path’s Master’s in Cybersecurity prepares students to step into the workforce and assume immediate responsibility for the management and oversight of such systems.

  https://www.kdnuggets.com/2022/07/baypath-prepared-manage-threat-ms-cybersecurity.html

• What is Text Classification?

  We will define text classification, how it works, some of its most known algorithms, and provide data sets that might help start your text classification journey.

  https://www.kdnuggets.com/2022/07/text-classification.html

• 90% of Today’s Code is Written to Prevent Failure, and That’s a Problem

  Trying to anticipate and defend against these failures is the constant uphill battle that today’s engineers are up against. But it doesn’t have to be.

  https://www.kdnuggets.com/2022/07/90-today-code-written-prevent-failure-problem.html

• K-nearest Neighbors in Scikit-learn

  Learn about the k-nearest neighbours algorithm, one of the most prominent workhorse machine learning algorithms there is, and how to implement it using Scikit-learn in Python.

  https://www.kdnuggets.com/2022/07/knearest-neighbors-scikitlearn.html

• Why Upskilling in Data Vis Matters (& How to Get Started)

  How do you condense the information you collect and present it to decision-makers in a clear, concise, and memorable way? This August, Noah Iliinsky will be opening up an intimate cohort and presenting an online course, Effective and Efficient Data Visualization.

  https://www.kdnuggets.com/2022/07/sphere-upskilling-data-vis-matters.html

• Best Practices for Creating Domain-Specific AI Models

  Here are some best practices and techniques for domain-specific model adaptation that worked for us time and again.

  https://www.kdnuggets.com/2022/07/best-practices-creating-domainspecific-ai-models.html

• Is Domain Knowledge Important for Machine Learning?

  If you incorporate domain knowledge into your architecture and your model, it can make it a lot easier to explain the results, both to yourself and to an outside viewer. Every bit of domain knowledge can serve as a stepping stone through the black box of a machine learning model.

  https://www.kdnuggets.com/2022/07/domain-knowledge-important-machine-learning.html

• KDnuggets News, July 27: The AIoT Revolution: How AI and IoT Are Transforming Our World • Introduction to Hill Climbing Algorithm

  Calculus for Data Science • Real-time Translations with AI • Using Numpy's argmax() • Using the apply() Method with Pandas DataFrames • An Introduction to Hill Climbing Algorithm in AI

  https://www.kdnuggets.com/2022/n30.html

• Detecting Data Drift for Ensuring Production ML Model Quality Using Eurybia

  This article will focus on a step-by-step data drift study using Eurybia an open-source python library

  https://www.kdnuggets.com/2022/07/detecting-data-drift-ensuring-production-ml-model-quality-eurybia.html

• Does the Random Forest Algorithm Need Normalization?

  Normalization is a good technique to use when your data consists of being scaled and your choice of machine learning algorithm does not have the ability to make assumptions on the distribution of your data.

  https://www.kdnuggets.com/2022/07/random-forest-algorithm-need-normalization.html

• Using Scikit-learn’s Imputer

  Learn about Scikit-learn’s SimpleImputer, IterativeImputer, KNNImputer, and machine learning pipelines.

  https://www.kdnuggets.com/2022/07/scikitlearn-imputer.html

• Top Posts July 18-24: Free Python Automation Course

  Free Python Automation Course • Machine Learning Algorithms Explained in Less Than 1 Minute Each • Parallel Processing Large File in Python • 12 Most Challenging Data Science Interview Questions • Decision Tree Algorithm, Explained

  https://www.kdnuggets.com/2022/07/top-posts-week-0718-0724.html

• Practical Deep Learning from fast.ai is Back!

  Looking for a great course to go from machine learning zero to hero quickly? fast.ai has released the latest version of Practical Deep Learning For Coders. And it won't cost you a thing.

  https://www.kdnuggets.com/2022/07/practical-deep-learning-fastai-2022.html

• The AIoT Revolution: How AI and IoT Are Transforming Our World

  The AIoT has the potential to transform industries and society, and it is already starting to have an impact. This article will explore the principles of AIoT, its benefits, and its current use.

  https://www.kdnuggets.com/2022/07/aiot-revolution-ai-iot-transforming-world.html

• The Difficulty of Estimating the Carbon Footprint of Machine Learning

  Is machine learning killing the planet? Probably not, but let's make sure it doesn't.

  https://www.kdnuggets.com/2022/07/difficulty-estimating-carbon-footprint-machine-learning.html

• Benefits Of Becoming A Data-First Enterprise

  Data is everywhere but only data is not sufficient to reap the benefits that come with it. It needs to be organized to enable the organizations to make more informed business decisions. In this article, we will learn what are the various benefits of being a data-first enterprise and using the data in developing a business intelligence solution.

  https://www.kdnuggets.com/2022/07/benefits-becoming-datafirst-enterprise.html

• An Introduction to Hill Climbing Algorithm in AI

  Hill climbing is basically a search technique or informed search technique having different weights based on real numbers assigned to different nodes, branches, and goals in a path.

  https://www.kdnuggets.com/2022/07/introduction-hill-climbing-algorithm-ai.html

• Using the apply() Method with Pandas Dataframes

  Explore ways in which you can use apply () method to do different activities in a DataFrame.

  https://www.kdnuggets.com/2022/07/apply-method-pandas-dataframes.html