DE & ML Digest
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Collection of all articles on Data Engineering and Machine Learning
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DE & ML Digest
119 subscribers
DE & ML Digest
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cCorrGAN: Conditional Correlation GAN for Learning Empirical Conditional Distributions in the…
Medium
cCorrGAN: Conditional Correlation GAN for Learning Empirical Conditional Distributions in the Elliptope
Generative Modelling in Finance: Motivation and Challenges
DE & ML Digest
ML
Differentiable Hardware
Medium
Differentiable Hardware
How AI Might Help Revive the Virtuous Cycle of Moore’s Law
DE & ML Digest
ML
Re-Imagine The Business Of Fashion: Part 2
Medium
Re-Imagine The Business Of Fashion: Part 2
Data Science can make the fashion industry become more sustainable. True or False?
DE & ML Digest
ML
Clean Up Data Noise with Fourier Transform in Python
Medium
Clean Up Data Noise with Fourier Transform in Python
Use Fourier Transform to clean up time series data in the shortest Python code
DE & ML Digest
ML
A Thousand Brains Theory: A Review
Medium
A Thousand Brains Theory: A Review
A new theory on intelligence and how the neocortex works.
DE & ML Digest
ML
Causal Inference in Data Science: Conditional Independence via Propensity Score Adjustment
Medium
Causal Inference in Data Science: Conditional Independence via Propensity Score Adjustment
Specification and Proofs of Propensity Scores, with Accompanied Computational Simulation
DE & ML Digest
ML
Detecting Outliers Using Python
Medium
Detecting Outliers Using Python
Using Isolation Forests for Automated Outlier Detection
DE & ML Digest
Big Data
Serving ML Models in Production: Common Patterns
reddit
Serving ML Models in Production: Common Patterns
Posted in r/bigdata by u/mgalarny • 1 point and 0 comments
DE & ML Digest
ML
Do frameworks have to be complicated to have value?
Medium
Do Your Frameworks Need to Be Intricate if You Want Big Value?
There’s a tightrope to be walked here in simplifying a construct, but not creating something so distilled that it becomes complicated…
DE & ML Digest
ML
Baseline Walkthrough for the Machine Translation Task of the Shifts Challenge at NeurIPS 2021
Medium
Baseline Walkthrough for the Machine Translation Task of the Shifts Challenge at NeurIPS 2021
Get yourself up and running!
DE & ML Digest
Big Data
[Перевод] Хранилища признаков: Сторона данных в конвеерах машинного обучения
Хабр
Хранилища признаков: Сторона данных в конвейерах машинного обучения
В этом посте представлен перевод статьи на Medium от Sarah Wooders , Peter Schafhalter , and Joey Gonzalez . Перевод подготовлен при поддержке сообщества аналитического курса DataLearn и...
DE & ML Digest
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Corporate Imperatives and the Future of AI Development, Part I
Medium
Corporate Imperatives and the Future of AI Development, Part I
What happens when AI research and development are co-opted by economic ideology and corporate data platforms?
DE & ML Digest
Big Data
An Ultimate Guide for Data Scientists
reddit
An Ultimate Guide for Data Scientists
Posted in r/bigdata by u/sharmaniti437 • 0 points and 0 comments
DE & ML Digest
ML
How to Deal with Missing Data using Python
Analytics Vidhya
How to Deal with Missing Data using Python
Due to Missing data, the statistical power of the analysis can reduce, which can impact the validity of the results. Let's handle missing data
DE & ML Digest
ML
Making Natural Language Processing easy with TextBlob
Analytics Vidhya
Making Natural Language Processing easy with TextBlob
TextBlob is a Python library for processing textual data. It provides a simple API for diving into common natural language processing tasks.
DE & ML Digest
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A Comprehensive Guide to PySpark RDD Operations
Analytics Vidhya
A Comprehensive Guide to PySpark RDD Operations
PySpark for efficient cluster computing in Python. Learn its syntax, RDD, and Pair RDD operations—transformations and actions simplified.
DE & ML Digest
ML
A Detailed Guide on Web Scraping using Python framework!
Analytics Vidhya
A Detailed Guide on Web Scraping using Python framework!
We'll look at how to use Python to implement web scraping. Web scraping is a way to extract vast volumes of data from websites
DE & ML Digest
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A Complete Guide on Docker for Beginners
Analytics Vidhya
A Complete Guide on Docker for Beginners
Docker is an extremely powerful containerization engine that makes building, managing and distributing applications efficient.
DE & ML Digest
ML
Text Summarization using the conventional, Hugging Face Transformer and Cosine Similarity
Analytics Vidhya
Text Summarization using the conventional, Hugging Face Transformer and Cosine Similarity
The goal of text summarization is to see if we can come up with a method that employs natural language processing to do so.
DE & ML Digest
ML
Generating Random Numbers and Arrays in Matlab and Numpy
Medium
Generating Random Numbers and Arrays in Matlab and Numpy
A comparison between Matlab and Numpy codes for reproducing random numbers and arrays
DE & ML Digest
ML
Building an End-to-End Logistic Regression Model
Analytics Vidhya
Logistic Regression Model: A Guide to Machine Learning Techniques and Applications
Discover Machine Learning, logistic regression, linear vs logistic, sigmoid, gradient descent, regularization, Python implementation, pros, cons.
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