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Collection of all articles on Data Engineering and Machine Learning
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DE & ML Digest
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DE & ML Digest
ML
Four Basic Steps in Data Preparation
KDnuggets
Four Basic Steps in Data Preparation - KDnuggets
What we would like to do here is introduce four very basic and very general steps in data preparation for machine learning algorithms. We will describe how and why to apply such transformations within a specific example.
DE & ML Digest
ML
Human Pose Estimation Using Machine Learning in Python
Analytics Vidhya
Human Pose Estimation Using Machine Learning in Python
In this article we understand Pose Estimation. Pose estimation is a computer vision technique to track the movements of a person or an object
DE & ML Digest
ML
Rapid Keyword Extraction (RAKE) Algorithm in Natural Language Processing
Analytics Vidhya
Rapid Keyword Extraction (RAKE) Algorithm in Natural Language Processing
Rapid Automatic Keyword Extraction(RAKE) is a Domain-Independent keyword extraction algorithm in Natural Language Processing.
DE & ML Digest
ML
kNN Algorithm – An Instance-based ML Model to Predict Heart Disease
Analytics Vidhya
kNN Algorithm - An Instance-based ML Model to Predict Heart Disease
In this article, we shall discuss kNN algorithm along with its practical implementation. It is one of the important instance based model
DE & ML Digest
ML
Exploring the noscript of a YouTube video through 2D projections of its bags of words
Medium
Exploring the noscript of a YouTube video through 2D projections of its bags of words
Applying PCA on the bags of words computed from the noscript to spread the video’s information on a 2D view.
DE & ML Digest
ML
How To Defeat The Machine Learning Engineer Impostor Syndrome
KDnuggets
How To Defeat The Machine Learning Engineer Impostor Syndrome - KDnuggets
How many times have you taken yet another online course on machine learning or read yet another paper on a new emerging topic, to be up-to-date in this crazy fast-paced AI/ML world -- only to keep feeling like an ML engineer impostor? These three personal…
DE & ML Digest
ML
Data Mesh — Fad or Fab?
Medium
Data Mesh — Fad or Fab?
Love it or hate it — it’s here. So, we turned to one of the experts to ask him some hard questions about the hottest topic in data.
DE & ML Digest
ML
No One Rung To Rule Them All:
Medium
No One Rung to Rule Them All: Addressing Scale and Expediency in Knowledge-Based AI
Cognitive AI, hierarchy of knowledge, and the answer to the unsustainable growth of all-inclusive deep-learning models
DE & ML Digest
ML
Accelerated TensorFlow model training on Intel Mac GPUs
Medium
Accelerated TensorFlow model training on Intel Mac GPUs
A mini-guide on how to train TensorFlow model on MacBook Pro dGPU via TensorFlow PluggableDevice
DE & ML Digest
ML
How to connect Airflow with a NiFi ETL-pipeline
Medium
How to connect Airflow with a NiFi ETL-pipeline
NiFi and Airflow are both powerful tools which are regularly in use in data projects, but using them together is not always easy.
DE & ML Digest
ML
UCL Data Science Society: Object Oriented Programming
Medium
UCL Data Science Society: Object Oriented Programming
What is OOP, defining a class, adding attributes, adding methods, and class inheritance
DE & ML Digest
ML
What Apple’s Weather App Can Teach us About Data Visualization
Medium
What Apple’s Weather App Can Teach us About Data Visualization
Three lessons that you can apply to your next visualization, dashboard, or presentation
DE & ML Digest
ML
The Shapley Value for ML Models
Medium
The Shapley Value for ML Models
What is a Shapley value, and why is it crucial to many explainability techniques?
DE & ML Digest
ML
Apply Instrumental Variables Method in Causal Analysis
Medium
Apply Instrumental Variables Method in Causal Analysis
With a focus on the experimentation illustrated by an example
DE & ML Digest
ML
Simple steps to create custom colormaps in Python
Medium
Simple steps to create custom colormaps in Python
Creating any colormap at your wills
DE & ML Digest
Big Data
Amazon RDS Custom for Oracle – New Control Capabilities in Database Environment
Amazon
Amazon RDS Custom for Oracle – New Control Capabilities in Database Environment | Amazon Web Services
Managing databases in self-managed environments such as on premises or Amazon Elastic Compute Cloud (Amazon EC2) requires customers to spend time and resources doing database administration tasks such as provisioning, scaling, patching, backups, and configuring…
DE & ML Digest
Big Data
Infrastructure and data issues hamper companies adopting AI, study finds
VentureBeat
Infrastructure and data issues hamper companies adopting AI, study finds
According to a new survey from Run:AI, companies are hampered in their AI adoption efforts by data and infrastructure issues.
DE & ML Digest
Big Data
AWS Local Zones Are Now Open in Las Vegas, New York City, and Portland
Amazon
AWS Local Zones Are Now Open in Las Vegas, New York City, and Portland | Amazon Web Services
Today, we are opening three new AWS Local Zones in Las Vegas, New York City (located in New Jersey), and Portland metro areas. We are now at a total of 14 Local Zones in 13 cities since Jeff Barr announced the first Local Zone in Los Angeles in December 2019.…
DE & ML Digest
Big Data
Apache Spark 3.2 Release: Main Features and What's New for Spark-on-Kubernetes - Data Mechanics Blog
reddit
Apache Spark 3.2 Release: Main Features and What's New for...
Posted in r/bigdata by u/JY-DataMechanics • 6 points and 0 comments
DE & ML Digest
ML
Transfer Learning: The Highest Leverage Deep Learning Skill You Can Learn.
Medium
Transfer Learning: The Highest Leverage Deep Learning Skill You Can Learn.
Transfer learning is an amazing way to speed up deep learning training. It helps solve complex problems with pre-existing knowledge.
DE & ML Digest
ML
The What, Why, and How of Model Drift
Medium
The What, Why, and How of Model Drift
Identifying types of model drift, detection techniques, preventative measures, and remedies
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