--- title: Best Daily Dose of Data Science | Avi Chawla | Substack... description: The most upvoted Daily Dose of Data Science | Avi Chawla | Substack posts from June 2024, curated by the daily.dev community. canonical: https://daily.dev/sources/dailydoseofds/best-of/2024/06 twitter:card: summary_large_image twitter:site: @dailydotdev og:url: https://daily.dev/sources/dailydoseofds/best-of/2024/06 og:type: website og:site_name: daily.dev og:title: Best Daily Dose of Data Science | Avi Chawla | Substack posts — June 2024 | daily.dev og:description: The most upvoted Daily Dose of Data Science | Avi Chawla | Substack posts from June 2024, curated by the daily.dev community. og:image: https://media.daily.dev/image/upload/s--VAY5ToZt--/f_auto/v1724209435/public/daily.dev%20-%20open%20graph --- # Best of Daily Dose of Data Science | Avi Chawla | Substack — June 2024 1. 1 [](https://daily.dev/posts/20-most-common-magic-methods-ru2lmidxx "20 Most Common Magic Methods") Article Daily Dose of Data Science | Avi Chawla | Substack · 2y 20 Most Common Magic Methods Discover the 20 most common magic methods used in Python OOP, including \_\_new\_\_, \_\_init\_\_, and \_\_str\_\_. Learn how to use these methods and their importance in Python projects. 146 5 2. 2 [](https://daily.dev/posts/4-ways-to-test-ml-models-in-production-f7zjv8aqg "4 Ways to Test ML Models in Production") Article Daily Dose of Data Science | Avi Chawla | Substack · 2y 4 Ways to Test ML Models in Production Testing ML models in production is crucial to ensure reliability and performance on real-world data. Four common strategies are A/B testing, canary testing, interleaved testing, and shadow testing. A/B testing distributes requests non-uniformly between models, while canary testing gradually rolls out the candidate model to a subset of users. Interleaved testing mixes predictions from both models, and shadow testing logs outputs without affecting user experience. These techniques help mitigate risks and validate the model effectively. 46 3. 3 [](https://daily.dev/posts/poisson-regression-vs-linear-regression-ymcnd17e5 "Poisson Regression vs. Linear Regression") Article Daily Dose of Data Science | Avi Chawla | Substack · 2y Poisson Regression vs. Linear Regression Linear regression may not be suitable for count data as it can produce negative predictions, which don't make sense for certain types of data like the number of calls received. Poisson regression, a type of generalized linear model (GLM), is better suited for count-based responses as it assumes the data follows a Poisson distribution. It ensures non-negative predictions and acknowledges that outcomes are not equally likely around the mean. 22 4. 4 [](https://daily.dev/posts/7-categorical-data-encoding-techniques-b9blqpgyk "7 Categorical Data Encoding Techniques") Article Daily Dose of Data Science | Avi Chawla | Substack · 2y 7 Categorical Data Encoding Techniques The post outlines seven techniques for encoding categorical data, including one-hot encoding, dummy encoding, effect encoding, label encoding, ordinal encoding, count encoding, and binary encoding. Each method is briefly explained along with the number of resulting features. The post also mentions the category-encoders library for more techniques and encourages reader interaction by asking for additional methods. 19 5. 5 [](https://daily.dev/posts/data-version-control-azffsm2hf "Data Version Control") Article Daily Dose of Data Science | Avi Chawla | Substack · 2y Data Version Control Data version control is a critical skill for data scientists working on ML projects. It helps with versioning large datasets, ensuring reproducibility and experiment traceability. Git is not suitable for versioning datasets due to file size limitations, and data version control solves this problem. 19 6. 6 [](https://daily.dev/posts/4-strategies-for-multi-gpu-training-w5tkqb8kd "4 Strategies for Multi-GPU Training") Article Daily Dose of Data Science | Avi Chawla | Substack · 2y 4 Strategies for Multi-GPU Training This post discusses four strategies for multi-GPU training: model parallelism, tensor parallelism, data parallelism, and pipeline parallelism. 18 [See all Daily Dose of Data Science | Avi Chawla | Substack archives](/sources/dailydoseofds/best-of) ```json {"@context":"https://schema.org","@graph":[{"@type":"Organization","@id":"https://daily.dev/#organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180},"sameAs":["https://twitter.com/dailydotdev","https://github.com/dailydotdev","https://www.linkedin.com/company/daily-dev-ltd"]},{"@type":"WebSite","@id":"https://daily.dev/#website","url":"https://daily.dev","name":"daily.dev","publisher":{"@id":"https://daily.dev/#organization"},"potentialAction":{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https://daily.dev/search?q={search_term_string}"},"query-input":"required name=search_term_string"}}]} {"@context":"https://schema.org","@graph":[{"@type":"CollectionPage","@id":"https://daily.dev/sources/dailydoseofds/best-of/2024/06#page","url":"https://daily.dev/sources/dailydoseofds/best-of/2024/06","name":"Best Daily Dose of Data Science | Avi Chawla | Substack Posts — June 2024","description":"The most upvoted Daily Dose of Data Science | Avi Chawla | Substack posts from June 2024, curated by the daily.dev community.","isPartOf":{"@type":"WebSite","url":"https://daily.dev"}},{"@type":"ItemList","@id":"https://daily.dev/sources/dailydoseofds/best-of/2024/06#items","numberOfItems":6,"itemListElement":[{"@type":"ListItem","position":1,"url":"https://daily.dev/posts/20-most-common-magic-methods-ru2lmidxx","name":"20 Most Common Magic Methods"},{"@type":"ListItem","position":2,"url":"https://daily.dev/posts/4-ways-to-test-ml-models-in-production-f7zjv8aqg","name":"4 Ways to Test ML Models in Production"},{"@type":"ListItem","position":3,"url":"https://daily.dev/posts/poisson-regression-vs-linear-regression-ymcnd17e5","name":"Poisson Regression vs. Linear Regression"},{"@type":"ListItem","position":4,"url":"https://daily.dev/posts/7-categorical-data-encoding-techniques-b9blqpgyk","name":"7 Categorical Data Encoding Techniques"},{"@type":"ListItem","position":5,"url":"https://daily.dev/posts/data-version-control-azffsm2hf","name":"Data Version Control"},{"@type":"ListItem","position":6,"url":"https://daily.dev/posts/4-strategies-for-multi-gpu-training-w5tkqb8kd","name":"4 Strategies for Multi-GPU Training"}]},{"@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https://daily.dev"},{"@type":"ListItem","position":2,"name":"Sources","item":"https://daily.dev/sources"},{"@type":"ListItem","position":3,"name":"Daily Dose of Data Science | Avi Chawla | Substack","item":"https://daily.dev/sources/dailydoseofds"},{"@type":"ListItem","position":4,"name":"Best of","item":"https://daily.dev/sources/dailydoseofds/best-of"},{"@type":"ListItem","position":5,"name":"June 2024"}]}]} ```