Data Science
Data Science | News, how-tos, features, reviews, and videos
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The high cost of data science toil
Data science toil saps agility and prevents organizations from scaling data science efforts efficiently and sustainably. Here’s how to avoid it.
Don’t rush to machine learning
A simpler approach—good data, SQL queries, if/then statements—often gets the job done.
JetBrains previews data science IDE
DataSpell offers data analysis and machine learning model prototyping.
What is AI bias mitigation, and how can it improve AI fairness?
Algorithmic biases that lead to unfair or arbitrary outcomes take many forms. But we also have many strategies and techniques to combat them.
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When RPA meets data science
Data science can make robotic process automation more intelligent. Robotic process automation make it easier to deploy data science models in production.
Data science needs drudges
Quality data science outputs depend on quality inputs. Data cleansing and preparing may not be exciting work, but it’s critical.
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An introduction to time series forecasting
Time series forecasts are used to predict a future value or a classification at a particular point in time. Here’s a brief overview of their common uses and how they are developed.
6 essential Python tools for data science—now improved
SciPy, Numba, Cython, Dask, Vaex, and Intel SDC all have new versions that aid big data analytics and machine learning projects.
The real successes of AI
Despite the hype, especially around self-driving cars, AI is writing code, designing Google chip floor plans, and telling us how much to trust it.
Getting started with time series analysis
Time series analysis involves identifying attributes of your time series data, such as trend and seasonality, by measuring statistical properties.
How the cloud and big compute are remaking HPC
High-performance computing projects require massive quantities of compute resources. Pairing simulation and specialized hardware with the cloud powers the breakthroughs of the future.
How to visualize time series data
Visualizing time series data is often the first step in observing trends that can guide time series modeling and analysis.
Simplify machine learning with Azure Applied AI Services
Microsoft is wrapping its Cognitive Services machine learning platform as business-focused services.
Speed up your Python with Numba
Want faster number-crunching in Python? You can speed up your existing Python code with the Numba JIT, often with only one instruction.
Get started with Anaconda Python
Anaconda provides a handy GUI, a slew of work environments, and tools to simplify the process of using Python for data science.
Why you need a data integration platform
With every organization generating and accessing multiple data sources, an integration platform ensures every team has the data they need to drive the business forward.
Excel, Python, and the future of data science
If the ubiquitous spreadsheet program is the gateway to data science, Python aims to be the next step.
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Use the new R pipe built into R 4.1
Learn the new pipe operator built into R 4.1 and how it differs from the maggritr pipe. Don’t want to install R 4.1 yet? See how to run R 4.1 in a Docker container.
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