2020-05-20

Guidelines to use Transfer Learning in Convolutional Neural Networks

9 mins read Transfer learning involves taking a pre-trained neural network and adapting the neural network to a new, different data set. Depending […]
2020-05-09

Installing g++ (C++ Compiler) on Windows

11 mins read Follow these steps to install g++ (the GNU C++ compiler) for Windows. There is no room for creativity here; you must […]
2020-05-02

Kalman Filter Simply Explained

5 mins read Let’s start with what a Kalman filter is: It’s a method of predicting the future state of a system based […]
2020-04-26

Common behavioral questions in job interviews

3 mins read 1. Getting to Know You What motivates you at work? Describe what your preferred supervisor—employee relationship looks like. What two […]
2020-04-26

A good LinkedIn profile checklist

3 mins read Here is a list of rules to make your LinkedIn profile professional: General Criteria Meet Specification Overall, profile is professional, […]
2020-02-21

Walkthrough of an exploratory analysis for classification problems

20 mins read In this post, I’ll outline how to perform an exploratory analysis for a binary classification problem. I am going to […]
2020-02-05

Dealing with imbalanced data in machine learning

8 mins read Imbalanced classes are a common problem in machine learning classification where there is a disproportionate ratio of observations in each […]
2020-02-03

List of useful tutorials for Exploratory Data Analysis (EDA)

< 1 min https://towardsdatascience.com/exploratory-data-analysis-8fc1cb20fd15 https://medium.com/omarelgabrys-blog/statistics-probability-exploratory-data-analysis-714f361b43d1 https://www.kaggle.com/ekami66/detailed-exploratory-data-analysis-with-python https://www.kaggle.com/dvigneshwer/kernele7f4dbb964/notebook Visualizing the distribution of a dataset — seaborn 0.10.0 documentationhttps://seaborn.pydata.org/tutorial/distributions.html https://www.kaggle.com/kashnitsky/topic-1-exploratory-data-analysis-with-pandas https://iq.opengenus.org/exploratory-data-analysis-python/ Plotting with categorical data […]
2020-02-03

Types of Data & Measurement Scales: Nominal, Ordinal, Interval and Ratio

6 mins read There are four measurement scales: nominal, ordinal, interval, and ratio. These are simply ways to categorize different types of variables […]
2020-01-30

Using Kaggle Datasets in Google Colab

< 1 min Steps: Create an API key in Kaggle.To do this, go to kaggle.com/ and open your user settings page.  Next, scroll […]
2020-01-30

Getting Started With Google Colab

5 mins read If you want to create a machine learning model but say you don’t have a computer that can take the […]
2020-01-30

Understanding Gated Recurrent Unit (GRU) with PyTorch code

21 mins read The Gated Recurrent Unit (GRU) is the younger sibling of the more popular Long Short-Term Memory (LSTM) network, and also a […]
2020-01-30

Understanding Long Short-Term Memory Networks (LSTM) with PyTorch codes

24 mins read LSTMs are a particular variant of RNNs, therefore having a grasp of the concepts surrounding RNNs will significantly aid your […]
2020-01-28

Recurrent Neural Networks (RNN) with PyTorch

22 mins read Recurrent Neural Networks(RNNs) have been the answer to most problems dealing with sequential data and Natural Language Processing(NLP) problems for […]
2020-01-28

A complete guide to Python’s magic methods with example

33 mins read Introduction What are magic methods? They’re everything in object-oriented Python. They’re special methods that you can define to add “magic” […]