Two months ago, I proposed the loan status data science challenge problem via a medium article. The goal was to get participants to attempt the problem and share their version of the solution.

Till date, I’ve had feedback from 5 participants. Before sharing the output from these participants, here is the problem statement for the exercise.

Model for forecasting loan status

Instructions: In this problem, you will forecast the outcome of a portfolio of loans. Each loan is scheduled to be repaid over 3 years and is structured as follows:

• First, the borrower receives the funds. This event is called the origination.
• The borrower then makes regular repayments until one of the following…

The helium atom is the simplest many-body system containing two electrons. Two describe the ground state of helium, we could simply ignore the Coulomb interaction between the electrons and treat the two electrons as independent. This would reduce the problem to the hydrogenic model. This approximation is known to produce a very large ground state energy, and hence an ionization energy inconsistent with the experimental value (24.6 eV).

Besides the independent electron approximation, other models that incorporate electron-electron interaction could be used. …

Data Science, Education

As a lifelong learner, I am constantly challenging myself to learn something new. In today’s world of information technology, there are unlimited learning resources on virtually any discipline or specialty. For me, the best place where I go to took for great courses to broaden my knowledge and to learn something new is massive open online courses (MOOCs).

MOOCs for the most part, are free online courses available for anyone to enroll. MOOCs provide an affordable and flexible way to learn new skills, advance your career and deliver quality educational experiences at scale. MOOCs cover a broad spectrum of online courses in leadership, analytics, data science, machine learning, professional skills, engineering, business & management, humanities, computer science, and much more. These courses are usually offered by top universities across the world like MIT, Harvard, UC Berkeley, University of Michigan, EPFL, Hong Kong Polytechnic University, The University of Queensland, and much more. Some courses are also offered by big corporations such as IBM, google, and Microsoft. The greatest advantage of MOOCs is the opportunity to learn from leaders and experts, and the privilege of taking courses from the world’s top universities. …

There are so many good packages and libraries that can be used for building predictive models or for producing data visualizations. Some of the most common packages for descriptive and predictive analytics include:

• Ggplot2
• Pandas
• Numpy
• Matplotlib
• Seaborn
• Scikit-learn
• Caret
• TensorFlow
• PyTorch
• Keras

Thanks to these packages, anyone can build a model or produce a data visualization. With the availability of packages and libraries, programming skills are no longer an essential requirement for beginners in data science. However, to be successful in data science, it is important to have some basic programming knowledge in order to be able to use the available packages and libraries efficiently for building reliable and accurate models. In this article, we discuss some basic programming skills required for successful data science practice. …

Quantum theory explains everything about the atom. An atom is by definition a bound state containing a single nucleus. Examples of atoms are Hydrogen (H), Helium (He), Lithium (Li), Beryllium (Be), Boron (B), Carbon(C), Nitrogen (N), Oxygen (O), Fluorine (F), and Neon (Ne). The nucleus of an atom is made of protons and neutrons. The nucleus of Hydrogen (the simplest atom) contains only a single proton. Since a proton is positively charged and a neutron is uncharged (neutral), the overall charge of the nucleus is positive. In fact the positive charge of the nucleus gives it its ability to attract electrons to form an atom. Since stable atoms carry an overall charge of zero, it means a nucleus has to bind to the appropriate number of electrons (negatively charged) in such a way that the total charge of the atom remains zero. For example, Hydrogen has one proton and one electron, Carbon has 6 protons and 6 electrons, and Oxygen has 8 protons and 8 electrons. Quantum mechanics tells us that electrons in an atom occupy certain discrete energy levels. The energy states closer to the nucleus are referred to as the core states. These states have very high binding energies. Only the electrons in states furthest away from the nucleus can participate in chemical reaction. These electrons are loosely bound and are referred to as the outer or valence electrons. …

Data Science

With so much to learn and so many advancements to follow in the field of data science, there are a core set of foundational concepts that remain essential. Twenty of these ideas are highlighted here that are key to review when preparing for a job interview or just to refresh your appreciation of the basics.

1. Dataset

Just as the name implies, data science is a branch of science that applies the scientific method to data with the goal of studying the relationships between different features and drawing out meaningful conclusions based on these relationships. Data is, therefore, the key component in data science. A dataset is a particular instance of data that is used for analysis or model building at any given time. A dataset comes in different flavors such as numerical data, categorical data, text data, image data, voice data, and video data. A dataset could be static (not changing) or dynamic (changes with time, for example, stock prices). Moreover, a dataset could depend on space as well. For example, temperature data in the United States would differ significantly from temperature data in Africa. …