Python for Machine Learning
Code Your First Machine Learning App
Introduction
Machine learning’s popularity has significantly increased over the last couple of years all over the world. More and more people from multiple backgrounds have taken the step of making a career change and/or exploring this promising field.
Programming boot camps are continuously gaining popularity, new academic programs are being offered at universities and colleges, and the community of researchers interested in this field is constantly growing, generating more knowledge and algorithms to tackle today’s problems.
While machine learning is a fascinating field, it can be intimidating at the beginning for someone without a strong background in math, probability, statistics, or…
Python for Data Science
Simple Guide to Read Databases using Python
Data Collection and Reading
The very first step in any data analytics, data science or machine learning project consists in collecting data. You might have to make some research to find it, conduct surveys, collect questionnaires, take samples, or retrieve it from different sources.
If you are lucky enough to start working in a given project or task whose data has already been collected, the following step would consist on reading such data to start its analysis (i.e. loading the data into your script or program).
There are multiple sources from which datasets can be read, including .csv (comma-separated values) files, .txt files, .xlsx…
Python for Industrial Engineers
Measuring Process Performance
Process Capability Analysis
Process capability analysis represents a significant component of the Measure phase from the DMAIC (Define, Measure, Analysis, Improve, Control) cycle during a Six Sigma project. This analysis measures how a process performance fits the customer’s requirements, which are translated into specification limits for the interesting characteristics of the product to be manufactured or produced. The results from this analysis may help industrial engineers identify variation within a process and develop further action plans that lead to better yield, lower variation, and fewer defects.
Specifications
Specifications are the voice of the customer. Every process should be capable of fulfilling the customer’s requirements…
SIMULATION MODELING
Choosing the Right Types of Simulation For Your Project
Before starting to build any simulation model for a given project, it becomes crucial to identify the types of simulation that best matches the system to be modeled.
Will the system evolve over time?
Will the system agents interact with each other’s and with their environment?
Will agents be capable of adapting to new conditions, thus changing their decision patterns? Is the system to be modeled it a dynamic or complex system?
In this blog, we will review the most popular types of simulation widely used by professionals and academics to conduct simulation studies.
Discrete Event Simulation (DES)
PYTHON FOR TEXT ANALYTICS
Analyzing Candidates Cover Letter for Jobs Openings
Introduction
Writing a strong cover letter is not a trivial task. It could either boost your application and make you more interesting for recruiters and hiring managers or disqualify you from the process. People spend a significant amount of time writing and formatting the perfect cover letter hoping it to be read by a talent acquisition professional and, eventually, help them land a job interview. Unfortunately, not all cover letters are actually ever seen by a human eye.
Due to the high number of applicants and resumes with cover letters submissions to job postings, manual resumes screening processes become tedious, ineffective…
PYTHON FOR INDUSTRIAL ENGINEERS
Quality Tools with Python
Pareto Chart
The Pareto chart, also known as the Pareto distribution diagram, is a vertical bar graph in which values are plotted in decreasing order of relative frequency from left to right. It represents an extremely useful tool during the first stages of analyzing a problem since it helps visualize what problems need attention first by looking at the tallest bars of the chart, which represent the variables with the greatest cumulative effect on a given system.
Developed by the Italian engineer Vilfredo Pareto, the chart provides a graphic representation of the Pareto principle, a theory maintaining that 80% of the output…
Python for Industrial Engineers
Interpreting Quality Control Charts
Quality Control Charts
Quality control charts represent a great tool for engineers to monitor if a process is under statistical control. They help visualize variation, find and correct problems when they occur, predict expected ranges of outcomes and analyze patterns of process variation from special or common causes.
Special causes of variation are detected on control charts by noticing certain types of patterns present on them. In order to truly seize the benefits of control charts, such patterns — and what they represent on a given process — must be recognized to find the reason behind special causes of variation. …
Simulation Modeling
Keys for Succeeding as a Simulation Modeler
Simulation Modeling
Simulation modeling is the process of replicating an existing (or potential) system into a simulation model using software and technology. Simulation models represent great resources for testing multiple systems hypothetical scenarios in risk-free environments while being able to manipulate their parameters, constraints and logic without having to incur in high costs.
However, even with the use of cutting-edge technologies and software, replicating a system into a simulation model represents a challenging task. …
Python for Industrial Engineers
Total Productive Maintenance
Reliability
Reliability is the probability that an item, product, machine or equipment will perform a required function for a given period of time, under certain operating conditions. In other words, it is the probability of a non-failure over time.
Simulation Modeling
Steps to make the best out of your simulation study
Simulation Modeling
Simulation is one of the most widely used operations research and management science techniques. It consists in the use of mathematical methods and computer techniques to imitate or simulate the operations of various kinds of real-world facilities and process, referred as systems. The assumptions of how a system works usually take the form of mathematical or logical relationships; they constitute a model that is used to try to gain understanding on how the corresponding system behaves.
Since most real-world systems are too complex to allow realistic models to be evaluated analytically, these models must be studied by means of simulation…
