- Occam’s Razor by Avinash Kaushik, examining web analytics and Digital Marketing.
- OpenGardens, Data Science for Internet of Things (IoT), by Ajit Jaokar.
- O’reilly Radar O’Reilly Radar, a wide range of research topics and books.
- Observational Epidemiology A college professor and a statistical consultant offer their comments, observations and thoughts on applied statistics, higher education and epidemiology.
- Overcoming bias By Robin Hanson and Eliezer Yudkowsky. Present Statistical analysis in reflections on honesty, signaling, disagreement, forecasting and the far future.
- Probability &
Python is almost a-must-have skill for data scientist, as you can see many data scientist positions require python programming skills. This post introduces some of the most popular python modules for data science. They are widely used to conducted projects related to data mining and machine learning, and normal data analysis.
SciPy. SciPy (pronounced “Sigh Pie”) is a Python-based ecosystem of open-source software for mathematics, science, and engineering. It provides a wide range of algorithms and mathematical tools for data scientist.
NumPy. NumPy is the fundamental package for scientific computing with Python.
Data Scientists get assigned different names in different organizations. Contrary to popular belief, data science is not entirely about numbers, though it is a lot about them. A statistician, an astrologer, a survey designer, a biostatistician all play a data scientist’s role at some point without being known as one.
There are a number of programming languages and software applications that support data analysis functions and they require different levels of programming skills. The following section explores different types of data scientists and corresponding functions performed by them:
7 Types of Data Scientist
1) Data Scientist as Statistician
This is data analysis in the traditional sense.[Read More...]
Here are some Data Science and Machine Learning related Interview Questions asked by big companies such as Facebook, Amazon, Microsoft, Yelp, Pinterest, Square, Google, Glassdoor and Groupon. I also post an article that briefly describes the popular machine learning interview questions.
1. Given a coin you don’t know it’s fair or unfair. Throw it 6 times and get 1 tail and 5 head. Determine whether it’s fair or not. What’s your confidence value?
2. Given Amazon data, how to predict which users are going to be top shoppers in this holiday season.