- MLOps Best Practices - Jul 29, 2021.
Many technical challenges must be overcome to achieve successful delivery of machine learning solutions at scale. This article shares best practices we encountered while architecting and applying a model deployment platform within a large organization, including required functionality, the recommendation for a scalable deployment pattern, and techniques for testing and performance tuning models to maximize platform throughput.
Best Practices, MLOps
- Unleashing the Power of MLOps and DataOps in Data Science - Jun 29, 2021.
Organizations trying to move forward with analytics and data science initiatives -- while floating in an ocean of data -- must enhance their overall approach and culture to embrace a foundation on DataOps and MLOps. Leveraging these operational frameworks are necessary to enable the data to generate real business value.
Best Practices, Data Science, DataOps, MLOps
- 15 common mistakes data scientists make in Python (and how to fix them) - Mar 3, 2021.
Writing Python code that works for your data science project and performs the task you expect is one thing. Ensuring your code is readable by others (including your future self), reproducible, and efficient are entirely different challenges that can be addressed by minimizing common bad practices in your development.
Best Practices, Data Scientist, Jupyter, Mistakes, Programming, Python
- Can Data Science Be Agile? Implementing Best Agile Practices to Your Data Science Process - Jan 18, 2021.
Agile is not reserved for software developers only -- that's a myth. While these effective strategies are not commonly used by data scientists today and some aspects of data science make Agile a bit tricky, the methodology offers plenty of benefits to data science projects that can increase the effectiveness of your process and bring more success to your outcomes.
Agile, Best Practices, Data Science, Development
Software Engineering Tips and Best Practices for Data Science - Oct 13, 2020.
Bringing your work as a Data Scientist into the real-world means transforming your experiments, test, and detailed analysis into great code that can be deployed as efficient and effective software solutions. You must learn how to enable your machine learning algorithms to integrate with IT systems by taking them out of your notebooks and delivering them to the business by following software engineering standards.
Best Practices, Data Science, Software Engineering, Tips
- 5 Best Practices for Putting Machine Learning Models Into Production - Oct 12, 2020.
Our focus for this piece is to establish the best practices that make an ML project successful.
Best Practices, Machine Learning, Production
- LinkedIn’s Pro-ML Architecture Summarizes Best Practices for Building Machine Learning at Scale - Sep 23, 2020.
The reference architecture is powering mission critical machine learning workflows within LinkedIn.
Best Practices, LinkedIn, Machine Learning, Scalability
- Computer Vision Recipes: Best Practices and Examples - Sep 2, 2020.
This is an overview of a great computer vision resource from Microsoft, which demonstrates best practices and implementation guidelines for a variety of tasks and scenarios.
Best Practices, Computer Vision, Microsoft, Python
- 5 Apache Spark Best Practices For Data Science - Aug 4, 2020.
Check out these best practices for Spark that the author wishes they knew before starting their project.
Apache Spark, Best Practices, Data Science
- Software engineering fundamentals for Data Scientists - Jun 30, 2020.
As a data scientist writing code for your models, it's quite possible that your work will make its way into a production environment to be used by the masses. But, writing code that is deployed as software is much different than writing code for exploratory data analysis. Learn about the key approaches for making your code production-ready that will save you time and future headaches.
Advice, Best Practices, Data Science, Programming, Software Engineering
- Five Lines of Code - Jun 24, 2020.
If you want to learn simple and practical rules for coding and refactoring, "Five Lines of Code" from Manning is the guide for you, teaching you concrete principles for refactoring. Save 40% with code nlfive40 until July 24.
Best Practices, Book, Manning, Programming
- Nitpicking Machine Learning Technical Debt - Jun 8, 2020.
Technical Debt in software development is pervasive. With machine learning engineering maturing, this classic trouble is unsurprisingly rearing its ugly head. These 25 best practices, first described in 2015 and promptly overshadowed by shiny new ML techniques, are updated for 2020 and ready for you to follow -- and lead the way to better ML code and processes in your organization.
Pages: 1 2
Best Practices, DevOps, Explainability, Interpretability, Machine Learning, Monitoring, Pipeline, Technical Debt, Version Control
- Taming Complexity in MLOps - May 28, 2020.
A greatly expanded v2.0 of the open-source Orbyter toolkit helps data science teams continue to streamline machine learning delivery pipelines, with an emphasis on seamless deployment to production.
Best Practices, Docker, MLOps, Python
- 10 Useful Machine Learning Practices For Python Developers - May 25, 2020.
While you may be a data scientist, you are still a developer at the core. This means your code should be skillful. Follow these 10 tips to make sure you quickly deliver bug-free machine learning solutions.
Best Practices, Machine Learning Engineer, Python
- KDnuggets™ News 20:n20, May 20: I Designed My Own ML and AI Degree; Automated Machine Learning: The Free eBook - May 20, 2020.
How to design your own AI & ML degree; Automated ML: The free ebook; Coding habits for data scientists; Cartoon: The Worst Telemedicine? Math for Programmers; and more.
AutoML, Best Practices, Free ebook, Machine Learning Education, Speech Recognition
- Coding habits for data scientists - May 14, 2020.
While the core machine learning algorithms might only take up a few lines of code, it's the rest of your program that can get messy fast. Learn about some techniques for identifying bad coding habits in ML that add to complexity in code as well as start new habits that can help partition complexity.
Best Practices, Data Scientist, Development, Jupyter, Programming
Natural Language Processing Recipes: Best Practices and Examples - May 1, 2020.
Here is an overview of another great natural language processing resource, this time from Microsoft, which demonstrates best practices and implementation guidelines for a variety of tasks and scenarios.
Best Practices, Microsoft, NLP, Python
- Reproducibility, Replicability, and Data Science - Nov 19, 2019.
As cornerstones of scientific processes, reproducibility and replicability ensure results can be verified and trusted. These two concepts are also crucial in data science, and as a data scientist, you must follow the same rigor and standards in your projects.
Best Practices, Data Science, Overfitting, Reproducibility, Trust, Validation
6 Key Concepts in Andrew Ng’s “Machine Learning Yearning” - Aug 12, 2019.
If you are diving into AI and machine learning, Andrew Ng's book is a great place to start. Learn about six important concepts covered to better understand how to use these tools from one of the field's best practitioners and teachers.
AI, Andrew Ng, Best Practices, Deployment, Machine Learning, Metrics, Training Data
- 12 Things I Learned During My First Year as a Machine Learning Engineer - Jul 23, 2019.
Learn about the day-in-the-life of one machine learning engineer and the important lessons learned for being successful in that role.
Advice, Best Practices, Communication, Machine Learning Engineer, Skills
- How to Build Disruptive Data Science Teams: 10 Best Practices - Jul 16, 2019.
Building a data science team from the ground up isn't easy. This strategic roadmap will help hiring managers with tactical advice and how to properly support a data science team once established.
Best Practices, Data Analyst, Data Engineer, Data Science Team, Data Scientist
- Approach pre-trained deep learning models with caution - Apr 23, 2019.
Pre-trained models are easy to use, but are you glossing over details that could impact your model performance?
Best Practices, Deep Learning, Training
The Best and Worst Data Visualizations of 2018 - Feb 8, 2019.
We reflect on some of the best examples of Data Visualization throughout 2018, before focussing on some of the not-so-good and how these can be improved.
Advice, Best Practices, Data Visualization, Failure, Sankey
- One-stop-learning-shop for data pros – get exclusive access for less than a cup of coffee - Dec 6, 2018.
TDWI Membership is the one-stop-learning-shop for data professionals, providing the necessary tools to move your career forward. Join in December for less than a cup of coffee.
Best Practices, Data Science Education, Salary, TDWI
- Top KDnuggets tweets, Nov 07-13: 10 Free Must-See Courses for Machine Learning and Data Science - Nov 14, 2018.
Also: Best Practices for Using Notebooks for #DataScience; Automated #MachineLearning - results of Gene Feruzza AutoML research.
Automated Machine Learning, Best Practices, Data Science, Machine Learning Education, Top tweets
- Best Practices for Using Notebooks for Data Science - Nov 8, 2018.
Are you interested in implementing notebooks for data science? Check out these 5 things to consider as you begin the process.
Best Practices, Data Science, Jupyter
- 7 Best Practices for Machine Learning on a Data Lake - Nov 7, 2018.
Download this report to learn about the data requirements for advanced analytics on a data lake, and best practices such analytics with a focus on machine learning.
Best Practices, Data Lake, Machine Learning, TDWI
Programming Best Practices For Data Science - Aug 7, 2018.
In this post, I'll go over the two mindsets most people switch between when doing programming work specifically for data science: the prototype mindset and the production mindset.
Best Practices, Data Science, Pandas, Programming, Python
- Products for Product People: Best Practices in Analytics, July 24 Webinar - Jul 19, 2018.
Learn product analytics best practices and the "meta" perspective from a practitioner who is building products that anybody, including product managers, can use to access, analyze, and act on data to make important decisions.
Analytics, Best Practices, Industry, Looker, Products
- Best Practices in Data Visualization, continued - Jun 6, 2018.
Do your data visualizations need a reboot? Though data visualizations may be designed to facilitate understanding, not all graphs are effective. In this webcast, viewers will learn how to use best practices to give a graph a makeover.
Best Practices, Data Visualization, JMP
- Introduction to Content Personalization - May 30, 2018.
The basics of user experience and content personalization. The way to target your audience more precisely and effectively.
Best Practices, Personalization
- Best Practices in Data Visualization - May 2, 2018.
Do your data visualizations need a reboot? Though data visualizations may be designed to facilitate understanding, not all graphs are effective. In this webcast, viewers will learn how to use best practices to give a graph a makeover.
Best Practices, Data Visualization, JMP
- Webcasts: Finding analytic solutions to real problems - Mar 6, 2018.
The Technically Speaking webcasts provides real-word case studies that deliver key insights on overcoming the challenges with your data collection, preparation, and analysis.
Best Practices, Customer Analytics, Dashboard, Data Visualization, JMP, Text Analysis
- Data Science and Big Data – Download Best Practices Report - Aug 7, 2017.
Download Best Practices Report: Data Science and Big Data - Enterprise Paths to Success, where our research team takes a look at experiences with and plans for big data and data science.
Best Practices, Big Data, Data Science, Enterprise, TDWI
- Stanford Webinar: Pitfalls of A/B Testing - Apr 21, 2017.
Join Ramesh Johari, Associate Professor, Stanford Department of Management Science & Engineering, as he discusses some common practices and pitfalls in A/B testing, Apr 26, 2017.
A/B Testing, Best Practices, Stanford
- 5 Best Practices for Big Data Security - Jun 9, 2016.
Lack of data security can not only result in financial losses, but may also damage the reputation of organizations. Take a look at some of the most important data security best practices that can reduce the risks associated with analyzing a massive amount of data.
Best Practices, Big Data, Security
- INFORMS Courses: Essential Practice Skills, Data Exploration and Visualization, November, Baltimore - Oct 5, 2015.
Two INFORMS courses teach Essential Practice Skills for High-Impact Analytics Projects (Nov 18-19) and Data Exploration & Visualization (Nov 10-11). Both courses are given at Johns Hopkins University, Baltimore, MD.
Baltimore, Best Practices, Data Exploration, Data Visualization, Freakalytics, INFORMS, MD, Skills
- KDnuggets™ News 15:n25, Aug 5: Largest Dataset Analyzed? Big Data & the Dog Question; Impact of IoT - Aug 5, 2015.
New Poll: Largest Dataset Analyzed/Data Mined?; Cartoon: Big Data and the dog question; Impact of IoT on Big Data Landscape; Data is Ugly - Tales of Data Cleaning.
Best Practices, Cartoon, Data Cleaning, Dataset, IoT, Poll
- Big Data Best-Practice Checklist for Small and Medium Enterprises - Jul 30, 2015.
As more and more companies getting into the competition, it is important for the SMEs to get Big Data right from the start. Learn, how you can make most of the big data analytics.
Best Practices, Big Data Analytics, Checklist, FICO
- 10 things statistics taught us about big data analysis - Feb 10, 2015.
There are 10 ideas in applied statistics are relevant for big data analysis, focusing on prediction accuracy, interactive analysis and more.
Best Practices, Big Data, Overfitting, Statistics
- Top KDnuggets tweets, Jan 7-8: Programming languages popularity by US state; Machine Learning best practices from Kaggle competitions - Jan 9, 2015.
Programming languages popularity by US state; Why Ayasdi Topological Data Analysis Works - real data frequently is nonlinear; Learning Data Science and Predictive Modeling at Your Own Pace; Great talk: Machine Learning best practices from Kaggle competitions.
Ayasdi, Best Practices, Data Science Education, Java, Kaggle, Programming Languages, Python
- Webinar: Learn Analytics Best Practices for Hadoop - Sep 17, 2014.
Learn how to overcome some of the main challenges of Hadoop and successfully implement your own advanced analytics in a big data Hadoop environment. Free RapidMiner Webinar, Oct 2.
Best Practices, Hadoop, Radoop, RapidMiner
- Data Mining Best Practices – coming to a city near you! - Mar 18, 2014.
The "Data Mining: Principles and Best Practices" course, presented by SAS and Elder Research, introduces you to the power and potential of data mining and shows you how to discover useful patterns and trends from data.
Best Practices, Boston-MA, Chicago-IL, Data Mining, Elder Research, New York-NY, San Francisco-CA, SAS
