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Detailed layout of a logistic regression algorithm with a project

Logistic regression is very popular in machine learning and statistics. It can work on both binary and multiclass classification very well. I wrote tutorials on both binary and multiclass classification with logistic regression before. This article will be focused on image classification with logistic regression.

If you are totally new to logistic regression, please go to this article first. This article has a detailed explanation of how a simple logistic regression algorithm works.

It will be helpful if you are familiar with logistic regression already. If not, I hope you will still understand the concepts here. …

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It’s a Rich Library. Start Using It Today

For R user ggplot2 is the most popular visualization library with a huge number of graphics available. It is simple to use and is able to generate complex plots with simple commands fast. For an R user, there is no reason to not work with ggplot2 for data visualization

As I mentioned earlier, a lot of options and graphics are available. Nobody can remember all of those. So, it is helpful to have a cheat sheet or guide in hand. …

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Working Smart

It takes a sizeable amount of time to prepare for a coding interview. There are so many different topics, data structures, and algorithms to go over. Recursion is one of the most important algorithm types. Because it is the basis for so many important algorithms like divide and conquers, graph algorithms, dynamic programming, some tree-based searching and sorting algorithms, and many more. It is unavoidable. So it is important to have some practice before going to a coding interview.

This article will focus on the basic questions on recursion that are very common and popular in basic coding interviews. If you search in Google, you will find most of these questions here and there out there anyway. I am just compiling some of the common patterns of interview questions here for you.

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Learn to Match Any Pattern. It is Easier Than You Think.

The regular expression is nothing but a sequence of characters that matches a pattern in a piece of text or a text file. It is used in text mining in a lot of programming languages. The characters of the regular expression are pretty similar in all the languages. But the functions of extracting, locating, detecting, and replacing can be different in different languages.

In this article, I will use R. But you can learn how to use the regular expression from this article even if you wish to use some other language. It may look too complicated when you do not know it. But as I mentioned at the top it is easier than you think it is. I will try to explain it as much as I can. …

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Photo by ALICE POLLET on Unsplash

Make Your Storytelling More Interesting

Python has a few data visualization library. Arguably matplotlib is the most popular and widely used library. I have several tutorial articles on matplotlib before. This article will focus on some advanced visualization techniques. These plots and charts will provide you with some extra tools to make your reports or presentations of data in a more efficient and interesting way.

I am assuming that you already have learned the basic plots and charts in Matplotlib. If you need a refresher on some of them, please go through this article first:

I will use several different datasets for this article because different kind of plots works for different types of data. But I will try to stick to the same dataset as much as I can. …

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Photo by Aristedes Carrera on Unsplash

Summarising and Visualizing the Data for Better Understanding Even If All the Variables Are Not Understandable

Exploratory data analysis is very basic. Sometimes it is necessary to just understand the data well. Sometimes it is dome before diving into the modeling. Anyway, a big dataset will have no use if it is not possible to extract the necessary information from it. This article will explain some techniques and visualization codes to extract important information from a dataset.

There is another aspect of exploratory data analysis. We are data scientists only, right? But data is coming from all different areas of life. There might a medical dataset, environmental dataset, or financial dataset where some or all of the terms are not known. …

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Photo by Allef Vinicius on Unsplash

Learning by Doing

Recursion is one of the very essential parts of programming. Many popular algorithms are dome in recursion. So, it has a lot of importance. If recursion is important, the analysis of the time complexity of a recursive algorithm is also important. In this article, I will explain a widely used method for calculating the time complexity of a recursion. That is the Master method.

One thing to remember here is, the master method is a method to solve a recurrence. But before that, a recurrence expression needs to be drawn from the algorithm.

I will start by showing how to draw a recurrence expression from a basic and well-known algorithm. And then will explain how to solve different recurrence expression using the master method with examples. …

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Photo by Brooke Cagle on Unsplash

Andrew Ng’s Machine Learning Course in Python

One of the most popular Machine-Leaning course is Andrew Ng’s machine learning course in Coursera offered by Stanford University. I tried a few other machine learning courses before but I thought he is the best to break the concepts into pieces make them very understandable.

But I think, there is just only one problem. That is, all the assignments and instructions are in Matlab. I am a Python user and did not want to learn Matlab. So, I just learned the concepts from the lectures and developed all the algorithms in Python.

I explained all the algorithms in my own way(as simply as I could) and demonstrated the development of almost all the algorithms in the different articles before. I thought I should summarise them all on one page so that if anyone wants to follow, it is easier for them. Sometimes a little help goes a long way. …

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Use Cases of Uniform, Normal, and Exponential Continuous Probability Distributions in R

Probability and the probability distribution is the base for mot statistical inference techniques, therefore machine learning, artificial intelligence, and data analytics. I wrote an overview of the discrete probability distribution methods and their R implementation before:

I promised at the end of the article above that I will write about the continuous probability distribution methods in another article. This is the one. In this article, I will try to provide a clear idea about some very common continuous probability distribution.

I will explain it in a very simple regular language not too much in mathematical or calculus terms and focus on Examples and R…

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Photo by Franciele Cunha on Unsplash

My Journey, Mistakes, and Learnings

This is very common to switch to data science. Most data scientists I know out there do not have a degree in data science. They switched from another area. I also know many people who are trying to switch from another major. I meet many people being confused if it is the right career track for them. Well, the decision is yours. Everyone may have a different journey and may have different opinions. In this article, I decided to share my own experience. …


Rashida Nasrin Sucky

Data Scientist and MS Student at Boston University. Read my blog:

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