Tag Archives: data science

Microsoft Weekly Data Science News for March 02, 2018

Here are the latest articles from Microsoft regarding cloud data science products and updates.

Conversations with future data scientists (YouTube Playlist)

Last week I spent some time chatting with future data scientists. I set up a camera to record some of the answers. Below are a few of the questions addressed.

  • How did I transition to data science?
  • Why start a data science project?
  • Should a new person focus on machine learning or deep learning?
  • What is an example data science project?
  • Why is real-time important?

Hopefully the videos and answers are helpful to others. Enjoy! And I kept most of the videos fairly short. If you enjoy the videos, please subscribe to the YouTube channel, Learn Data Science. Also, if you have a question you would like answered, please leave a comment below.

Data Science Live Book

Pablo Casas has published a book freely available online, Data Science Live Book. To quote from the book,

It is a book about data preparation, data analysis and machine learning.

The book is open source, and the code examples are written in R.

Learn Data Science Youtube Channel

Transitioning to a career in data science can be full of unanswered questions. I am here to help you get answers to those questions.

Today, I am launching a new Youtube Channel, Learn Data Science. I will select a question and make a video providing an answer. I will provide some of the answers, and I may have some guests answer the questions as well.

If you have any questions about becoming a data scientist, please leave a comment.

Columbia University Applied Machine Learning Online

Columbia University’s course Applied Machine Learning Spring 2018 by Andreas C. Müller has all the lecture notes, slides, homework, and videos posted online.

Andreas is also the author of the book Introduction to Machine Learning with Python.

Microsoft Weekly Data Science News for February 23, 2018

Today, I am starting a new weekly series where I will share the latest news related to Microsoft Cloud Data Science Products along with the supplied discription. Disclaimer: I did not author any of these posts, but I wanted to share them.

4 Steps to Finding Your Data

So, you have identified a fascinating new problem to solve with data. You correctly started with a problem and not the data. It seems both beneficial and interesting. Now where do you get the data? Here are 4 steps (in order) for how to find data.

1. Existing Data

The best place to start is the data you currently have. What data does your organization currently collect? How can you get access to that? Start there.

2. OpenData

Then look for industry specific open data (data that is freely available). Many industries publish data monthly or yearly. Also, data is frequently available with government funded research. If industry specific data is not available, what other related data is openly available? It is often beneficial to augment your existing data with open data. Here are some lists of open data, Open Data, Part 1, Open Data, Part 2. There are also many others available.

3. API

Next, explore the opportunity of using an API to access data. Many application have existing API access. An API (Application Programming Interface) allows a person to write some computer code to pull machine-readable data from an existing system. Some are freely available, others have associated costs. Many allow the data to be available in near real-time. There are numerous API’s available where you can pull in data. Check with some of your existing applications. They are available for weather, stocks, news, social media, web analytics, and many more.

4. Create The Data

The last resort is to begin the creation of data. An obvious choice is to create a survey. Be careful because surveys can be trickier than initially thought. You often do not get good representation and the result is biased data. Another way to collect data is to change your application to begin collecting the desired information. You may even have to build a new application. Sometimes an entire process needs to be created or modified to include methods to collect the data. This last step usually takes the longest and costs the most money.

Tips for Data Science Students – FB Live

Awhile ago, I recorded a Facebook Live on Tips for Data Science Students. It goes along with the following post: Getting the most from your Data Science Masters Program.

Go After Your Data Science Dreams – Demystify Data Science Presentation 2017

Stick around for the Question and Answers at the end of the presentation where I talk about starting your own blog or entering Kaggle contests.

All of the other talks were great as well. You can register here Demystify Data Science Conference 2017 by Metis to get free access to all the other video presentations.

The Future of Data Science – Specialization

I have recently been exploring with creating YouTube Live Videos. Go to the Data Science 101 Facebook page to know more.