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Tag: Data Analysis

Why and How I use generators in python
Photo by David Carboni (https://unsplash.com/photos/xvkSnspiETA) on Unsplash (https://unsplash.com) Generators are very powerful feature in python and help you write better and organized code. WHY...
Why Jorge Prefers Dataquest Over DataCamp for Learning Data Analysis
When Jorge Varade decided he wanted to learn data analysis, he tried both DataCamp and Dataquest, and found he strongly preferred the latter. Here's why. The post Why Jorge Prefers Dataquest Over DataCamp for Learning Data Analysis appeared first on Dataquest.
Who is a Next-Gen Data Scientist?
A next-gen data scientist (www.thedsa.in) is a multi-disciplinary person who uses math, programming/technology, domain expertise to solve business problems using the available data. The demand for...
Learning R | Part 2 | Variables & Functions
Variables & Functions in R
Learning R | Part 1 | Basics of R & RStudio
Why R? Understanding RStudio
How to Become a Data Scientist?
Data science is all about clarifying goals, examining assumptions, evaluating evidence and assessing conclusions
Artificial Intelligence VS Machine Learning VS Data Science
This article states the basic difference between Difference between Artificial Intelligence (AI), Machine Learning (ML) and Data Science.
Top Trends for Data Science in 2019
Everywhere you look, we have new fads and concepts for the new year. This article is going to be rather different.Its all about the new trends in Data Science.
Analyzing Robinhood trade history
A Python script to get a look at your trading history from trading options and individual equities on Robinhood: calculate profit/loss, sum dividend payouts and generate buy-and-hold comparison.
How Big Data Is Helping To Lower Medical Liability Risks
Practice economics are impacted by medical liability risks. Patient quality and efficiency is key to the healthcare industry’s success, but a lack of proper staffing has led to a fast-paced environment where medical liability remains a concern. Data collection is being utilized as a means to help lower these risks, …
Hitchhiker's guide to Exploratory Data Analysis
Hitchhiker's guide to Exploratory Data Analysis is a complete guide to get you started in the field of Data Science. Learn about Python libraries and how to architect questions to get conclusive results from the data.
3 Ways AI In The Business World Can Lead To Industry Improvement
Dartmouth held the first artificial intelligence (AI) conference in 1956. The idea of artificial intelligence gained popularity, and people believed machines would replace human beings in the workplace someday. However, at that time the idea lacked funding at its conceptual stage and could not develop, launching a period known as …
Why Choosing Python For Data Science Is An Important Move
In this article, we are going to discuss about why to choose Python for data science. We’ll introduce PixieDust, an open source library, that focuses on three simple goals: Democratize data science by lowering the barrier to entry for non-data scientists Increase collaboration between developers and data scientists Make it …
DIFFERENCE BETWEEN DATA SCIENCE, DATA ANALYTICS AND MACHINE LEARNING
So, it’s 2018 and the word is spread about Data boom. There are Tech Giants like Facebook, Amazon, and Google constantly working in the field of Machine learning and Data science. We all know that Machine learning, Data Sciences, and Data analytics is the future.
Handling Imbalanced Classes in the Dataset
What is Imbalanced Dataset ? The dataset may contain uneven samples /instances , so that it makes the algorithm to predict with accuracy of 1.0 each time u run the model. For example, if u have...
Pandas Tutorial 2: Aggregation and Grouping
Let’s continue with the pandas tutorial series. This is the second episode, where I’ll introduce aggregation (such as min, max, sum, count, etc.) and grouping. Both are very... The post Pandas Tutorial 2: Aggregation and Grouping appeared first on Data36.
Pandas Tutorial 1: Pandas Basics (Reading Data Files, DataFrames, Data Selection)
Pandas is one of the most popular Python libraries for Data Science and Analytics. I like to say it’s the “SQL of Python.” Why? Because pandas helps you... The post Pandas Tutorial 1: Pandas Basics (Reading Data Files, DataFrames, Data Selection) appeared first on Data36.
My Thoughts on Synthetic Data
A (relatively) brief introductory analysis on the effectiveness of synthesizing data for machine learning.