Deep Learning is highly empirical domain which majorly focusses on fine tuning the various parameters. The choice of these parameters defines the accuracy of model. So, it becomes important to choose such parameters wisely. Choosing the parameters based on intuition...
Introduction Data scientists are the no. 1 most promising job in America for 2019, according to a Thursday report from LinkedIn. Hence, this comes as no surprise: Data scientist topped Glassdoor’s list of Best Jobs in America for the past three years, with...
Introduction Evaluation metrics have a correlation with machine learning tasks. The tasks of classification, regression, ranking, clustering, topic modelling, etc, all have different metrics. Some metrics, such as precision, recall, are of use for multiple tasks....
Introduction Technology has become the embedded component of applications and the defacto driver for growth in industries. With the advent of AI, new milestones are being achieved each day. We are moving towards an era of more and more integration, making it an...
Introduction In computer science, Decision tree learning uses a decision tree (as a predictive model) to go from observations about an item to conclusions about the item’s target value. It is one of the predictive modelling approaches used in statistics, data mining...
Introduction As organizations turn to digital transformation strategies, they are also increasingly forming teams around the practice of Data Science. Currently, the main challenge for many CIOs, CDOs, and other Chief Data Scientists consist of positioning the Data...
Introduction With the growth of Data science in recent years, we have seen a growth in the development of the tools for it. R and Python have been steady languages used by people worldwide. But before R and Python, there was only one key player and it was MATLAB....
Data Science Competency Traditionally speaking, interviews are the bane of the IT world and it's no secret that most interview methods that are commonly used are flawed. They favor problem-solving skills while not measuring things much more important like teamwork...
Python and R have been around for well over 20 years. Python was developed in 1991 by Guido van Rossum, and R in 1995 by Ross Ihaka and Robert Gentleman. Both Python and R have seen steady growth year after year in the last two decades. Will that trend continue, or...
Introduction Time series analysis is the use of statistical methods to analyze time series data and extract meaningful statistics and characteristics of the data. In this blog, we will begin our journey of learning time series forecasting using python. We will be...