Job search is a tedious process involving going through numerous job pages and lengthy job descriptions and summaries. In this article, I will try to make this process a bit easier for you using Python’s Beautiful Soup and Word cloud library. We will extract information like job title, company name, location, job summary and description. […]
AI has become an integral part of our daily lives. It’s in our cars, telling us when it’s time for the engine to be serviced based on our driving patterns; it’s in our everyday Google searches and the suggestions from Amazon that follow us around on the web; it’s the chatbot on the end of […]
So far, we have explored the data using various descriptive statistics techniques and also dealt with missing values and outliers. It may seem that we are done with all the data pre-processing and preparation, and ready to apply one of the ML algorithms. Unfortunately, we are still far from simply applying any ML algorithm. Wondering […]
Jupyter notebook is an interactive web-based application used for capturing the whole computation process – developing, documenting, and executing code. Jupyter notebook is a part of the larger Jupyter project that also includes jupyter hub and jupyter lab. Jupyter notebook supports kernels in many languages like python, pyspark, R, Julia among a few. Jupyter notebooks […]
Well, there is no straightforward and sure shot answer to this question. The answer depends on many factors like the problem statement and the kind of output you want, type and size of the data, the available computational time, number of features and observations in the data, to name a few. Here are some important […]
In the last blog, we discussed the importance of the data cleaning process in a data science project and ways of cleaning the data to convert a raw dataset into a useable form. Here, we are going to talk about how to identify and treat the missing values in the data step by step. Real-world […]
The Green Revolution during the 1950s and 1960s remarkably drove up the global food production around the world, saving a billion people from starvation. The revolution led to the adoption of new technologies like high-yielding varieties (HYVs) of cereals, chemical fertilizers and agro-chemicals, better irrigation and mechanization of cultivation methods. India followed suite and adopted […]
In the last few blogs, we saw how to summarise and analyse the data using statistical methods and visualisations. But the raw data need to be processed to convert it into a usable shape. Data Preparation is the most important and foremost part of Data Science. It involves data pre-processing and data wrangling. Raw data […]
Continuing with the last series of blogs, in this, we are going to explore graphical ways of representing descriptive statistics. We have learnt that we can get the measures of central tendency and dispersion to understand the centre and spread of the features (a variable is a feature in a dataset). It is easy […]
“If you don’t like to read, you haven’t found the right book.” – J.K. Rowling Well, this is absolutely true in my case. I had never read a book outside of my school curriculum ever before I stumbled upon the Harry Potter series. The books beautifully depict the adventurous journey of little novice magicians to […]
