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• Learning Python in Four Weeks: A Roadmap

  Here is a roadmap for learning Python in four weeks, a combination of curated resources and ChatGPT prompts to master the language.

  https://www.kdnuggets.com/2023/02/learning-python-four-weeks-roadmap.html

• Why Data Scientists Expect Flawed Advice From Google Bard

  First reported by Reuters, Bard returned an inaccurate response, leading to a drop in Alphabet’s (GOOGL) stock price by as much as 9% on the day of the demonstration. For many in the data community, this did not come as a surprise; here’s why.

  https://www.kdnuggets.com/2023/02/data-scientists-expect-flawed-advice-google-bard.html

• Making Intelligent Document Processing Smarter: Part 1

  This article attempts to measure the effect of various noises present in scanned documents on the performance of various APIs in the OCR segment.

  https://www.kdnuggets.com/2023/02/making-intelligent-document-processing-smarter-part-1.html

• Learn Data Engineering From These GitHub Repositories

  Kickstart your Data Engineering career with these curated GitHub repositories.

  https://www.kdnuggets.com/2023/02/learn-data-engineering-github-repositories.html

• KDnuggets News, January 25: ChatGPT as a Python Programming Assistant • Python and Machine Learning to Predict Football Match Winners

  ChatGPT as a Python Programming Assistant • How to Use Python and Machine Learning to Predict Football Match Winners • 20 Questions (with Answers) to Detect Fake Data Scientists: ChatGPT Edition, Part 1 • From Data Collection to Model Deployment: 6 Stages of a Data Science Project • 5 Free Data Science Books You Must Read in 2023

  https://www.kdnuggets.com/2023/n03.html

• From Data Collection to Model Deployment: 6 Stages of a Data Science Project

  Here are 6 stages of a novel Data Science Project; From Data Collection to Model in Production, backed by research and examples.

  https://www.kdnuggets.com/2023/01/data-collection-model-deployment-6-stages-data-science-project.html

• Scaling Data Management Through Apache Gobblin

  Software companies can manage big data at a hyper-scale on different infrastructure stacks using Apache Gobblin.

  https://www.kdnuggets.com/2023/01/scaling-data-management-apache-gobblin.html

• Data Lakes and SQL: A Match Made in Data Heaven

  In this article, we will discuss the benefits of using SQL with a data lake and how it can help organizations unlock the full potential of their data.

  https://www.kdnuggets.com/2023/01/data-lakes-sql-match-made-data-heaven.html

• Overcome Your Data Quality Issues with Great Expectations

  Bad data costs organizations money, reputation, and time. Hence it is very important to monitor and validate data quality continuously.

  https://www.kdnuggets.com/2023/01/overcome-data-quality-issues-great-expectations.html

• Beginner’s Guide to Cloud Computing

  Learn how cloud computing works, different types of models, top cloud platforms, and applications.

  https://www.kdnuggets.com/2023/01/beginner-guide-cloud-computing.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

• Unsupervised Disentangled Representation Learning in Class Imbalanced Dataset Using Elastic Info-GAN

  This рареr attempts to exploit primarily twо flaws in the Infо-GАN рареr while retаining the оther good qualities improvements.

  https://www.kdnuggets.com/2023/01/unsupervised-disentangled-representation-learning-class-imbalanced-dataset-elastic-infogan.html

• 7 Super Cheat Sheets You Need To Ace Machine Learning Interview

  Revise the concepts of machine learning algorithms, frameworks, and methodologies to ace the technical interview round.

  https://www.kdnuggets.com/2022/12/7-super-cheat-sheets-need-ace-machine-learning-interview.html

• YOLOv5 PyTorch Tutorial

  Learn and train object detection model using YOLOv5.

  https://www.kdnuggets.com/2022/12/yolov5-pytorch-tutorial.html

• The Complete MLOps Study Roadmap

  Kickstart your career as an MLOps Engineer with this study roadmap.

  https://www.kdnuggets.com/2022/12/complete-mlops-study-roadmap.html

• How to Set Yourself Apart from Other Applicants with Data-Centric AI

  This article is designed to help you prepare for the job market and get yourself noticed in the industry.

  https://www.kdnuggets.com/2022/12/set-apart-applicants-datacentric-ai.html

• Learn modern forecasting techniques to help predict future business outcomes

  Help optimize business processes by predicting future outcomes using time series forecasting techniques. How? Join other professionals and learn from leading experts Tim Januschowski and Jan Gasthaus in their live online course starting January 17.

  https://www.kdnuggets.com/2022/12/sphere-learn-modern-forecasting-techniques-help-predict-future-business-outcomes.html

• How I Got 4 Data Science Offers and Doubled My Income 2 Months After Being Laid Off

  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.

  https://www.kdnuggets.com/2021/01/data-science-offers-doubled-income-2-months.html

• An Introduction to SMOTE

  Improve the model performance by balancing the dataset using the synthetic minority oversampling technique.

  https://www.kdnuggets.com/2022/11/introduction-smote.html

• Efficiency Spells the Difference Between Biological Neurons and Their Artificial Counterparts

  Part 8 of the series explores a single facet of biological neurons which, so far, have kept them way ahead of their artificial counterparts: their efficiency.

  https://www.kdnuggets.com/2022/11/efficiency-spells-difference-biological-neurons-artificial-counterparts.html

• Top Data Analyst Certification Courses for 2022

  Top certification courses by IBM, Edureka, DataCamp, Udacity, and Google.

  https://www.kdnuggets.com/2022/11/top-data-analyst-certification-courses-2022.html

• How To Create An Effective AI Strategy

  This post elaborates on various factors that go into consideration while prioritizing various AI initiatives.

  https://www.kdnuggets.com/2022/11/create-effective-ai-strategy.html

• 9 Skills You Need to Become a Data Engineer

  A data engineer is a fast-growing profession with amazing challenges and rewards. Which skills do you need to become a data engineer? In this post, we’ll take a look at both hard and soft skills.

  https://www.kdnuggets.com/2021/03/9-skills-become-data-engineer.html

• The Gap Between Deep Learning and Human Cognitive Abilities

  How do we bridge this gap between deep learning and human cognitive ability?

  https://www.kdnuggets.com/2022/10/gap-deep-learning-human-cognitive-abilities.html

• Machine Learning on the Edge

  Edge ML involves putting ML models on consumer devices where they can independently run inferences without an internet connection, in real-time, and at no cost.

  https://www.kdnuggets.com/2022/10/machine-learning-edge.html

• Top 10 MLOps Tools to Optimize & Manage Machine Learning Lifecycle

  As more businesses experiment with data, they realize that developing a machine learning (ML) model is only one of many steps in the ML lifecycle.

  https://www.kdnuggets.com/2022/10/top-10-mlops-tools-optimize-manage-machine-learning-lifecycle.html

• 10 Cheat Sheets You Need To Ace Data Science Interview

  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.

  https://www.kdnuggets.com/2022/10/10-cheat-sheets-need-ace-data-science-interview.html

• 11 Questions About Data Engineers: What’s the profession about, and where’s it heading?

  I hope my answers will be useful to novice data engineers and anyone interested in data engineering.

  https://www.kdnuggets.com/2022/10/11-questions-data-engineers-profession-heading.html

• Key-Value Databases, Explained

  Among the four big NoSQL database types, key-value stores are probably the most popular ones due to their simplicity and fast performance. Let’s further explore how key-value stores work and what are their practical uses.

  https://www.kdnuggets.com/2021/04/nosql-explained-understanding-key-value-databases.html

• Top 5 Machine Learning Practices Recommended by Experts

  This article is intended to help beginners improve their model structure by listing the best practices recommended by machine learning experts.

  https://www.kdnuggets.com/2022/09/top-5-machine-learning-practices-recommended-experts.html

• Lessons from a Senior Data Scientist

  The aim of this article was for me to gain a deeper insight into the life of a senior data scientist and how their experience can be used as lessons for up-and-coming data scientists.

  https://www.kdnuggets.com/2022/09/lessons-senior-data-scientist.html

• KDnuggets News, September 21: 7 Machine Learning Portfolio Projects to Boost the Resume • Free SQL and Database Course

  7 Machine Learning Portfolio Projects to Boost the Resume • Free SQL and Database Course • Top 5 Bookmarks Every Data Analyst Should Have • 7 Steps to Mastering Python for Data Science • 5 Concepts You Should Know About Gradient Descent and Cost Function

  https://www.kdnuggets.com/2022/n37.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

• 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

• 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

• 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

• 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

• 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

• 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

• 5 Project Ideas to Stay Up-To-Date as a Data Scientist

  The skills you have need maintenance and occasional updates. Doing an interesting data science project is what will keep you from getting rusty.

  https://www.kdnuggets.com/2022/07/5-project-ideas-stay-uptodate-data-scientist.html

• MLOps: The Key To Pushing AI Into The Mainstream

  In this blog, we will aim at discussing the reasons that make MLOps an essential aspect of pushing AI mainstream. Besides, we will highlight the capabilities of MLOps as a catalyst for AI implementation.

  https://www.kdnuggets.com/2022/07/mlops-key-pushing-ai-mainstream.html

• 10 Modern Data Engineering Tools

  Learn about the modern tools for data orchestration, data storage, analytical engineering, batch processing, and data streaming.

  https://www.kdnuggets.com/2022/07/10-modern-data-engineering-tools.html

• The Complete Collection of Data Science Interviews – Part 2

  The second part covers the list of Data Management, Data Engineering, Machine Learning, Deep Learning, Natural Language Processing, MLOps, Cloud Computing, and AI Manager interview questions.

  https://www.kdnuggets.com/2022/06/complete-collection-data-science-interviews-part-2.html

• Generate Synthetic Time-series Data with Open-source Tools

  An introduction to the generative adversarial network model DoppelGANger, and how you can use a new open-source PyTorch implementation of it to create high-quality synthetic time-series data.

  https://www.kdnuggets.com/2022/06/generate-synthetic-timeseries-data-opensource-tools.html

• Every Engineer Should and Can Learn Machine Learning

  Read this interview with Sourabh Bajaj of co:rise, discussing the evolution of the ML role, how he designed the course to connect with today’s business needs, and how he thinks students can apply the covered topics at the end of each course!

  https://www.kdnuggets.com/2022/06/corise-every-engineer-learn-machine-learning.html

• Learn MLOps with This Free Course

  Learn to train and track your experiments, create ML pipelines, model deployment, monitor the performance in production, and adopt best practices from DevOps.

  https://www.kdnuggets.com/2022/06/learn-mlops-free-course.html

• Free Data Engineering Courses

  Get into the highly in-demand world of data engineering for free and earn 6 figures salary.

  https://www.kdnuggets.com/2022/05/free-data-engineering-courses.html

• The Complete Collection of Data Science Books – Part 1

  Read the best books on Programming, Statistics, Data Engineering, Web Scraping, Data Analytics, Business Intelligence, Data Applications, Data Management, Big Data, and Cloud Architecture.

  https://www.kdnuggets.com/2022/05/complete-collection-data-science-books-part-1.html

• oBERT: Compound Sparsification Delivers Faster Accurate Models for NLP

  Discover "compound sparsification" and how to apply it to BERT models for 10x compression and GPU-level latency on commodity CPUs.

  https://www.kdnuggets.com/2022/05/obert-compound-sparsification-delivers-faster-accurate-models-nlp.html

• 4 Steps for Managing a Data Science Project

  Good planning and preparation will not only improve productivity, but it will help avoid potential pitfalls and roadblocks that could be encountered during project execution.

  https://www.kdnuggets.com/2022/05/4-steps-managing-data-science-project.html

• An Overview of Mercury: Creating Data Science Portfolio and Notebook Based WebApps

  Turn your dull Jupyter notebooks into interactive web apps by adding a YAML header and sharing it with your friends and colleagues. You can also use Mercury to create your data science portfolio, which consists of a resume and projects.

  https://www.kdnuggets.com/2022/05/overview-mercury-creating-data-science-portfolio-notebook-based-webapps.html

• Software Developer vs Software Engineer

  The terms developer and engineer are used synonymously, making it difficult to understand the difference between the two in the midst of a conversation.

  https://www.kdnuggets.com/2022/05/software-developer-software-engineer.html

• Top 5 Free Cloud Notebooks in 2022

  Create and collaborate on data science projects or train machine learning models using free cloud Jupyter notebook platforms. You get a hassle-free IDE experience and free compute resources.

  https://www.kdnuggets.com/2022/04/top-5-free-cloud-notebooks-2022.html

• Building a Scalable ETL with SQL + Python

  This post will look at building a modular ETL pipeline that transforms data with SQL and visualizes it with Python and R.

  https://www.kdnuggets.com/2022/04/building-scalable-etl-sql-python.html

• Prioritizing Data Science Models for Production

  Statistical performance metrics aren’t enough to pick the right models to bring to market.

  https://www.kdnuggets.com/2022/04/prioritizing-data-science-models-production.html

• Guide to Iteratively Tuning GNNs

  This blog walks through a process for experimenting with hyperparameters, training algorithms and other parameters of Graph Neural Networks.

  https://www.kdnuggets.com/2022/04/sigopt-guide-iteratively-tuning-gnns.html

• Top YouTube Channels for Learning Data Science

  YouTube has become an important element in people's self-development and increase of knowledge. Check out this list of YouTube channels that offer Data Science learning.

  https://www.kdnuggets.com/2022/04/top-youtube-channels-learning-data-science.html

• KDnuggets News, April 13: Python Libraries Data Scientists Should Know in 2022; Naïve Bayes Algorithm: Everything You Need to Know

  Python Libraries Data Scientists Should Know in 2022; Naïve Bayes Algorithm: Everything You Need to Know; Data Ingestion with Pandas: A Beginner Tutorial; Data Science Interview Guide - Part 1: The Structure; 5 Ways to Expand Your Knowledge in Data Science Beyond Online Courses

  https://www.kdnuggets.com/2022/n15.html

• The Complete Collection Of Data Repositories – Part 2

  Check out the collection of the best data repositories on healthcare, natural language, neuroscience, physics, social network, sports, time series, transportation, miscellaneous, and super data repositories.

  https://www.kdnuggets.com/2022/04/complete-collection-data-repositories-part-2.html

• Uncertainty Quantification in Artificial Intelligence-based Systems

  The article summarizes the plethora of UQ methods using Bayesian techniques, shows issues and gaps in the literature, suggests further directions, and epitomizes AI-based systems within the Financial Crime domain.

  https://www.kdnuggets.com/2022/04/uncertainty-quantification-artificial-intelligencebased-systems.html

• People Management for AI: Building High-Velocity AI Teams

  Practical advice for managers and directors who are looking to build AI/ML teams.

  https://www.kdnuggets.com/2022/03/people-management-ai-building-highvelocity-ai-teams.html

• Time Series Forecasting with Ploomber, Arima, Python, and Slurm

  In this blog you will see how the authors took a raw .ipynb notebook that does time series forecasting with Arima, modularized it into a Ploomber pipeline, and ran parallel jobs on Slurm.

  https://www.kdnuggets.com/2022/03/time-series-forecasting-ploomber-arima-python-slurm.html

• MLOps Is a Mess But That’s to be Expected

  In this post, I want to focus the discussion about the state of machine learning operations (MLOps) today, where we are, where we are going.

  https://www.kdnuggets.com/2022/03/mlops-mess-expected.html

• A New Way of Managing Deep Learning Datasets

  Create, version-control, query, and visualize image, audio, and video datasets using Hub 2.0 by Activeloop.

  https://www.kdnuggets.com/2022/03/new-way-managing-deep-learning-datasets.html

• KDnuggets News 22:n12, March 23: Best Data Science Books for Beginners; Linear vs Logistic Regression: A Succinct Explanation

  Best Data Science Books for Beginners; Linear vs Logistic Regression: A Succinct Explanation; Why Are So Many Data Scientists Quitting Their Jobs?; Feature Stores for Real-time AI & Machine Learning; How to Generate Tabular Synthetic Dataset

  https://www.kdnuggets.com/2022/n12.html

• Feature Stores for Real-time AI & Machine Learning

  Real-time AI/ML is on the rise and feature stores are key to successfully deploying them. Read on to see how the choice of online store and the feature store architecture play important roles in determining its performance and cost.

  https://www.kdnuggets.com/2022/03/feature-stores-realtime-ai-machine-learning.html

• From Google Colab to a Ploomber Pipeline: ML at Scale with GPUs

  In this short blog, we’ll review the process of taking a POC data science pipeline (ML/Deep learning/NLP) that was conducted on Google Colab, and transforming it into a pipeline that can run parallel at scale and works with Git so the team can collaborate on.

  https://www.kdnuggets.com/2022/03/google-colab-ploomber-pipeline-ml-scale-gpus.html

• AI-Generated Sports Highlights: Different Approaches

  Competition for viewers’ attention is not over after the players leave the field. Now, anyone who can put up a highlight compilation or a game summarization first gets the edge. So, let’s talk about how media companies do just that — with the help of Artificial Intelligence.

  https://www.kdnuggets.com/2022/03/aigenerated-sports-highlights-different-approaches.html

• How To Use Synthetic Data To Overcome Data Shortages For Machine Learning Model Training

  It takes time and considerable resources to collect, document, and clean data before it can be used. But there is a way to address this challenge – by using synthetic data.

  https://www.kdnuggets.com/2022/03/synthetic-data-overcome-data-shortages-machine-learning-model-training.html

• How Long Does It Take to Learn Data Science Fundamentals?

  This article discusses 2 levels of data science learning, and the amount of time that will need to go into each. From 6 months to 4 years, this write-up covers a number of skills and how long it takes to acquire them.

  https://www.kdnuggets.com/2022/03/long-take-learn-data-science-fundamentals.html

• Data Science: Reality vs Expectations

  In the majority of companies, the executives in charge of data science and the decision-making process using data science, have little or no education or understanding in actual data science. Where does this leave you, the data scientist?

  https://www.kdnuggets.com/2022/03/data-science-reality-expectations.html

• 5 Data Science Projects to Learn 5 Critical Data Science Skills

  Learn these to take any data science project idea from brainstorm to deployment.

  https://www.kdnuggets.com/2022/03/5-data-science-projects-learn-5-critical-data-science-skills.html

• Build a Machine Learning Web App in 5 Minutes

  In this article, you will learn to export your models and use them outside a Jupyter Notebook environment. You will build a simple web application that is able to feed user input into a machine learning model, and display an output prediction to the user.

  https://www.kdnuggets.com/2022/03/build-machine-learning-web-app-5-minutes.html

• Cloud Storage Adoption is the Need of the Hour for Business

  The rush towards cloud storage means that the cloud has to offer a valuable proposition to businesses. Let’s explore why businesses regardless of their size should consider moving to the cloud.

  https://www.kdnuggets.com/2022/02/cloud-storage-adoption-need-hour-business.html

• Essential Machine Learning Algorithms: A Beginner’s Guide

  Machine Learning as a technology, ensures that our current gadgets and their software get smarter by the day. Here are the algorithms that you ought to know about to understand Machine Learning’s varied and extensive functionalities and their effectiveness.

  https://www.kdnuggets.com/2021/05/essential-machine-learning-algorithms-beginners.html

• The Complete Collection of Data Science Cheat Sheets – Part 2

  A collection of cheat sheets that will help you prepare for a technical interview on Data Structures & Algorithms, Machine learning, Deep Learning, Natural Language Processing, Data Engineering, Web Frameworks.

  https://www.kdnuggets.com/2022/02/complete-collection-data-science-cheat-sheets-part-2.html

• From Oracle to Databases for AI: The Evolution of Data Storage

  From Oracle, to NoSQL databases, and beyond, read about data management solutions from the early days of the RBDMS to those supporting AI applications.

  https://www.kdnuggets.com/2022/02/oracle-databases-ai-evolution-data-storage.html

• Free MIT Courses on Calculus: The Key to Understanding Deep Learning

  Calculus is the key to fully understanding how neural networks function. Go beyond a surface understanding of this mathematics discipline with these free course materials from MIT.

  https://www.kdnuggets.com/2020/07/free-mit-courses-calculus-key-deep-learning.html

• Ploomber vs Kubeflow: Making MLOps Easier

  This article covers some background on Ploomber, Kubeflow pipelines, and why we need those tools to make our lives easier.

  https://www.kdnuggets.com/2022/02/ploomber-kubeflow-mlops-easier.html

• The Complete Collection of Data Science Cheat Sheets – Part 1

  A collection of cheat sheets that will help you prepare for a technical interview, assessment tests, class presentation, and help you revise core data science concepts.

  https://www.kdnuggets.com/2022/02/complete-collection-data-science-cheat-sheets-part-1.html

• Deploying a Streamlit WebApp to Heroku using DAGsHub

  Transform your machine learning models into a web app and share them with your friends and colleagues.

  https://www.kdnuggets.com/2022/02/deploying-streamlit-webapp-heroku-dagshub.html

• Data Warehousing with Snowflake for Beginners

  This tutorial provides only a brief synopsis of the data warehouse in Snowflake, which we will go through in more detail.

  https://www.kdnuggets.com/2022/02/data-warehousing-snowflake-beginners.html

• How to Successfully Deploy Data Science Projects

  This guide will provide detailed insight into the steps you can take to successfully manage your data science projects.

  https://www.kdnuggets.com/2022/01/successfully-deploy-data-science-projects.html

• Celebrating Awareness of the Importance of Data Privacy

  January 28 is Data Privacy Day, bringing awareness of the basic foundation and principles of data protection. Read about the day itself, why data privacy is important, and best practices you can adhere to in order to help ensure the privacy of your data.

  https://www.kdnuggets.com/2022/01/celebrating-awareness-importance-data-privacy.html

• How to Set Up Your Data Science Stack on a Budget

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

  https://www.kdnuggets.com/2022/01/data-science-stack-budget.html

• 6 Data Science Technologies You Need to Build Your Supply Chain Pipeline

  Here are some of the data science technologies needed to build a comprehensive and smooth supply chain pipeline.

  https://www.kdnuggets.com/2022/01/6-data-science-technologies-need-build-supply-chain-pipeline.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

• How to Process a DataFrame with Millions of Rows in Seconds

  TLDR; process it with a new Python Data Processing Engine in the Cloud.

  https://www.kdnuggets.com/2022/01/process-dataframe-millions-rows-seconds.html

• A Full End-to-End Deployment of a Machine Learning Algorithm into a Live Production Environment

  How to use scikit-learn, pickle, Flask, Microsoft Azure and ipywidgets to fully deploy a Python machine learning algorithm into a live, production environment.

  https://www.kdnuggets.com/2021/12/deployment-machine-learning-algorithm-live-production-environment.html

• The Story of the Women in Data Science (WiDS) Datathon

  The author shares their experience of almost winning the competition and the things they have learned from the failures. Learn more about the WiDS Datathon and tips on winning the next challenge.

  https://www.kdnuggets.com/2022/01/story-women-data-science-wids-datathon.html

• Deliver a Killer Presentation in Data Science Interviews

  How to present yourself as a strong candidate in interview presentations.

  https://www.kdnuggets.com/2022/01/deliver-killer-presentation-data-science-interviews.html

• 11 Best Companies to Work for as a Data Scientist

  This list of best data science companies aims to go beyond the usual and expected. Some great and perhaps underrated options to get a job as a data scientist.

  https://www.kdnuggets.com/2021/12/11-best-companies-work-data-scientist.html

• How AI/ML Technology Integration Will Help Business in Achieving Goals in 2022

  AI/ML systems have a wide range of applications in a variety of industries and sectors, and this article highlights the top ways AI/ML will impact your small business in 2022.

  https://www.kdnuggets.com/2021/12/aiml-technology-integration-help-business-achieving-goals-2022.html

• 6 Predictive Models Every Beginner Data Scientist Should Master">6 Predictive Models Every Beginner Data Scientist Should Master

  Data Science models come with different flavors and techniques — luckily, most advanced models are based on a couple of fundamentals. Which models should you learn when you want to begin a career as Data Scientist? This post brings you 6 models that are widely used in the industry, either in standalone form or as a building block for other advanced techniques.

  https://www.kdnuggets.com/2021/12/6-predictive-models-every-beginner-data-scientist-master.html

• Hands-On Reinforcement Learning Course, Part 1

  Start your learning journey in Reinforcement Learning with this first of two part tutorial that covers the foundations of the technique with examples and Python code.

  https://www.kdnuggets.com/2021/12/hands-on-reinforcement-learning-course-part-1.html

• How to Speed Up XGBoost Model Training

  XGBoost is an open-source implementation of gradient boosting designed for speed and performance. However, even XGBoost training can sometimes be slow. This article will review the advantages and disadvantages of each approach as well as go over how to get started.

  https://www.kdnuggets.com/2021/12/speed-xgboost-model-training.html

• Cloud ML In Perspective: Surprises of 2021, Projections for 2022

  Let’s take a closer look on Cloud ML market in 2021 in retrospective (with occasional drills into realities of 2020, too). Read this in-depth analysis.

  https://www.kdnuggets.com/2021/12/cloud-ml-perspective-surprises-2021-projections-2022.html

• My First Six Months as a Data Scientist

  The technical and non-technical lessons I’ve learned.

  https://www.kdnuggets.com/2021/12/first-six-months-data-scientist.html

• Analyzing Scientific Articles with fine-tuned SciBERT NER Model and Neo4j

  In this article, we will be analyzing a dataset of scientific abstracts using the Neo4j Graph database and a fine-tuned SciBERT model.

  https://www.kdnuggets.com/2021/12/analyzing-scientific-articles-finetuned-scibert-ner-model-neo4j.html

• A Beginner’s Guide to End to End Machine Learning

  Learn to train, tune, deploy and monitor machine learning models.

  https://www.kdnuggets.com/2021/12/beginner-guide-end-end-machine-learning.html

• How to Use Permutation Tests

  A walkthrough of permutation tests and how they can be applied to time series data.

  https://www.kdnuggets.com/2021/12/use-permutation-tests.html

• KDnuggets™ News 21:n45, Dec 1: Most Common SQL Mistakes on Data Science Interviews; Why Machine Learning Engineers are Replacing Data Scientists

  Most Common SQL Mistakes on Data Science Interviews; Why Machine Learning Engineers are Replacing Data Scientists; Vote in new KDnuggets Poll: What Percentage of Your Machine Learning Models Have Been Deployed? KDnuggets: Personal History and Nuggets of Experience.

  https://www.kdnuggets.com/2021/n45.html

• Sentiment Analysis API vs Custom Text Classification: Which one to choose?

  In this article, we are going to compare the sentiment extraction performance between Sentiment Analysis engines and Custom Text classification engines. The idea is to show pros and cons of these two types of engines on a concrete dataset.

  https://www.kdnuggets.com/2021/11/sentiment-analysis-api-custom-text-classification.html

• Why Machine Learning Engineers are Replacing Data Scientists">Why Machine Learning Engineers are Replacing Data Scientists

  The hiring run for data scientists continues along at a strong clip around the world. But, there are other emerging roles that are demonstrating key value to organizations that you should consider based on your existing or desired skill sets.

  https://www.kdnuggets.com/2021/11/why-machine-learning-engineers-are-replacing-data-scientists.html

• Stop Blaming Humans for Bias in AI

  Can artificial intelligence be rid of bias? This is an important question, and it’s equally important that we look in the right place for the answer.

  https://www.kdnuggets.com/2021/11/stop-blaming-humans-bias-ai.html

• eBook: 101 Ways to Use Third-Party Data to Make Smarter Decisions

  To guide you in becoming a data-driven organization, AWS Data Exchange has created a new eBook, 101 Ways to Use Third-Party Data to Make Smarter Decisions. Learn how to transform the ‘currency’ of data into actionable business insights.

  https://www.kdnuggets.com/2021/11/roidna-ebook-101-ways-third-party-data-smarter-decisions.html

• Anecdotes from 11 Role Models in Machine Learning

  The skills needed to create good data are also the skills needed for good leadership.

  https://www.kdnuggets.com/2021/11/anecdotes-11-role-models-machine-learning.html

• What Comes After HDF5? Seeking a Data Storage Format for Deep Learning

  In this article we are discussing that HDF5 is one of the most popular and reliable formats for non-tabular, numerical data. But this format is not optimized for deep learning work. This article suggests what kind of ML native data format should be to truly serve the needs of modern data scientists.

  https://www.kdnuggets.com/2021/11/after-hdf5-data-storage-format-deep-learning.html

• Design Patterns for Machine Learning Pipelines">Design Patterns for Machine Learning Pipelines

  ML pipeline design has undergone several evolutions in the past decade with advances in memory and processor performance, storage systems, and the increasing scale of data sets. We describe how these design patterns changed, what processes they went through, and their future direction.

  https://www.kdnuggets.com/2021/11/design-patterns-machine-learning-pipelines.html

• Salary Breakdown of the Top Data Science Jobs">Salary Breakdown of the Top Data Science Jobs

  Machine Learning vs NLP vs Data Engineer vs Data Scientist, and what it means to be in each role.

  https://www.kdnuggets.com/2021/11/salary-breakdown-top-data-science-jobs.html

• Advanced PyTorch Lightning with TorchMetrics and Lightning Flash

  In this tutorial we will be diving deeper into two additional tools you should be using: TorchMetrics and Lightning Flash. TorchMetrics unsurprisingly provides a modular approach to define and track useful metrics across batches and devices, while Lightning Flash offers a suite of functionality facilitating more efficient transfer learning and data handling, and a recipe book of state-of-the-art approaches to typical deep learning problems.

  https://www.kdnuggets.com/2021/11/advanced-pytorch-lightning-torchmetrics-lightning-flash.html

• Analyze Python Code in Jupyter Notebooks

  We present a new tool that integrates modern code analysis techniques with Jupyter notebooks and helps developers find bugs as they write code.

  https://www.kdnuggets.com/2021/10/analyze-python-code-jupyter-notebooks.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

• Training BPE, WordPiece, and Unigram Tokenizers from Scratch using Hugging Face

  Comparing the tokens generated by SOTA tokenization algorithms using Hugging Face's tokenizers package.

  https://www.kdnuggets.com/2021/10/bpe-wordpiece-unigram-tokenizers-using-hugging-face.html

• Data Scientist vs Data Engineer Salary">Data Scientist vs Data Engineer Salary

  What are the differences between these two popular tech roles?

  https://www.kdnuggets.com/2021/10/data-scientist-data-engineer-salary.html

• KDnuggets™ News 21:n40, Oct 20: The 20 Python Packages You Need For Machine Learning and Data Science; Ace Data Science Interviews with Portfolio Projects

  The 20 Python Packages You Need For Machine Learning and Data Science; How to Ace Data Science Interview by Working on Portfolio Projects; Deploying Your First Machine Learning API; Real Time Image Segmentation Using 5 Lines of Code; What is Clustering and How Does it Work?

  https://www.kdnuggets.com/2021/n40.html

• Serving ML Models in Production: Common Patterns

  Over the past couple years, we've seen 4 common patterns of machine learning in production: pipeline, ensemble, business logic, and online learning. In the ML serving space, implementing these patterns typically involves a tradeoff between ease of development and production readiness. Ray Serve was built to support these patterns by being both easy to develop and production ready.

  https://www.kdnuggets.com/2021/10/serving-ml-models-production-common-patterns.html

• Amazon Web Services Webinar: Leverage data sets to create a customer-centric strategy and improve business outcomes

  Register now for this webinar, Oct 28, to learn how using third-party data enhances applications to better prioritize your target customer - helping you build a more customer-centric business.

  https://www.kdnuggets.com/2021/10/roidna-aws-webinar-customer-centric-strategy.html

• The Evolution of Tokenization – Byte Pair Encoding in NLP

  Though we have SOTA algorithms for tokenization, it's always a good practice to understand the evolution trail and learning how have we reached here. Read this introduction to Byte Pair Encoding.

  https://www.kdnuggets.com/2021/10/evolution-tokenization-byte-pair-encoding-nlp.html

• Introduction to PyTorch Lightning">Introduction to PyTorch Lightning

  PyTorch Lightning is a high-level programming layer built on top of PyTorch. It makes building and training models faster, easier, and more reliable.

  https://www.kdnuggets.com/2021/10/introduction-pytorch-lightning.html

• Advanced Statistical Concepts in Data Science

  The article contains some of the most commonly used advanced statistical concepts along with their Python implementation.

  https://www.kdnuggets.com/2021/09/advanced-statistical-concepts-data-science.html

• Building a Structured Financial Newsfeed Using Python, SpaCy and Streamlit

  Getting started with NLP by building a Named Entity Recognition(NER) application.

  https://www.kdnuggets.com/2021/09/-structured-financial-newsfeed-using-python-spacy-and-streamlit.html

• Path to Full Stack Data Science">Path to Full Stack Data Science

  Start your journey toward mastering all aspects of the field of Data Science with this focused list of in-depth self-learning resources. Curated with the beginner in mind, these recommendations will help you learn efficiently, and can also offer existing professionals useful highlights for review or help filling in any gaps in skills.

  https://www.kdnuggets.com/2021/09/path-full-stack-data-science.html

• Nine Tools I Wish I Mastered Before My PhD in Machine Learning">Nine Tools I Wish I Mastered Before My PhD in Machine Learning

  Whether you are building a start up or making scientific breakthroughs these tools will bring your ML pipeline to the next level.

  https://www.kdnuggets.com/2021/09/nine-tools-mastered-before-phd-machine-learning.html

• Don’t Touch a Dataset Without Asking These 10 Questions

  Selecting the right dataset is critical for the success of your AI project.

  https://www.kdnuggets.com/2021/09/dataset-asking-10-questions.html

• What Is The Real Difference Between Data Engineers and Data Scientists?

  To launch your data career, you’ll need both theoretical knowledge and applied skills. Bootcamp programs like Springboard’s Data Science Career Track and Data Engineering Career Track can help make you job-ready through hands-on, project-based learning and one-on-one mentorship. Wondering which data career path is right for you? Read on to find out.

  https://www.kdnuggets.com/2021/09/springboard-difference-data-engineers-data-scientists.html

• Adventures in MLOps with Github Actions, Iterative.ai, Label Studio and NBDEV

  This article documents the authors' experience building their custom MLOps approach.

  https://www.kdnuggets.com/2021/09/adventures-mlops-github-actions-iterative-ai-label-studio-and-nbdev.html

• Amazon Web Services Webinar: Boost customer satisfaction and sales with consumer insights data

  Join this webinar, Sep 27, to learn how to leverage external data to understand market needs and consumer behavior – helping you build a more customer-centric business.

  https://www.kdnuggets.com/2021/09/roidna-aws-webinar-consumer-insights-data.html

• Data Scientists Without Data Engineering Skills Will Face the Harsh Truth">Data Scientists Without Data Engineering Skills Will Face the Harsh Truth

  Although the role of the data scientist is still evolving, data remains at its core. Setting the right expectations for what you will do as a data scientist is important, and, to be sure, knowing the tools of data engineering will get yourself ready for the real world.

  https://www.kdnuggets.com/2021/09/data-scientists-data-engineering-skills.html

• The Prefect Way to Automate & Orchestrate Data Pipelines

  I am migrating all my ETL work from Airflow to this super-cool framework.

  https://www.kdnuggets.com/2021/09/prefect-way-automate-orchestrate-data-pipelines.html