Jingwen Zheng - page 14

This blog presents the Coursera project "catch the pink flamingo". Here, you can find the data model design like classification, clustering, and the histogram made by splunk.

Since big data becomes more and more important in our life. As a fresh graduate in Economics and Statistics, I’m eager to learn more knowledge about big data. Thus, I decide to participate the course Big Data specilization, created by University of California, San Diego, taught by Ilkay Altintas (Chief Data Science Officer), Amarnath Gupta (Dire...

Since the internship will be finished in a few days, I’m seeking employment and received several invitations of interview, one of these company is FABERNOVEL DATA & MEDIA. After the first telephone interview, there was a data-analysis test, which is really interesting. Thus, I would like to share with you. Data There are 288,425 observatio...

For the end of master, I’m doing my internship at French Development Agency as a data analyst in Guarantee Division (GAR), which offers guarantees to banks providing loans to SMEs, thus limiting their risks. In order to record the business operation of GAR, we have several databases. Thus, during this internship, my principal mission is accordi...

Nowadays, technique plays an important role in our life, almost all of us search and get information on website. However, as a data analyst, it’s important to read, understand and explain the website performance, which can contribute to business of company. However, building such a framework is always complicated and taking long time. Fortunatel...

Applying decision tree model in R's library 'rpart', using rpart function to build a model, showing fancyRpartPlot example, predicting with predict(), pruning with prune().

As I mentioned in my blog “What is Machine Learning”, Machine Learning tasks are typically classified into three broad categories, one of them is Supervised learning. In the supervised learning setting, it is important to understand the concept of two sets: Training set and Test set, which are useful to make good predictions about unseen observa...

Machine learning explores the study and construction of algorithms that can learn from and perform predictive analysis on data. Such algorithms operate by building a model from an example training set of input observations in order to make data-driven predictions or decisions expressed as outputs, rather than following strictly static program in...