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The more you share, the more you learn. This quote motivated me to share my own experiences in Data Science to the world, especially those coming from non-tech background. At that time, I thought that if my post even helps one person, it would be worth it. To my surprise, once I started writing articles, many people contacted me through LinkedIn, telling me about how my article helped them. This motivated me to share more and here I am making a sort of repository for links to all articles. I hope you enjoy it!!
Feel free to connect with me @ LinkedIn to discuss articles or share your opinion.

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Master Python for Data Science

“Information is the oil of the 21st century, and analytics is the combustion engine.” — Peter Sondergaard, Gartner. Ever wondered why you see advertisements on Youtube or Facebook or Google sites related to your current searches? Don’t you think these ads make you buy luxury products more instead of necessary ones?

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Dynamic Dashboards using Google Data Studio

Whenever we come across any datasets, we see thousands or even millions of rows of data that do not make any sense. But this data has a lot of hidden potentials that can be discovered by a specialist. These specialists generally use data visualization tools to analyze data and draw insights from the data. Excel, Tableau, Google Data Studio, PowerBI, Python libraries like Seaborn, Matplotlib, etc. are some commonly used tools.

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How to make an impressive Data Science Portfolio?

Gone are the days, when people just used to view CV and decide whether you’re a suitable candidate for an internship or job. In the technological sector, people now see the overall profile and projects (Portfolio) to shortlist candidates, especially for Data Science.

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Decision Trees using Sklearn

With decision trees, AI can make well-thought decisions without any human interference. Decision trees is a supervised learning algorithm which is used to solve both regression and classification problems. It is a predictive modelling approach that gives a graphical representation of decisions and every possible outcome because of that decision.

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Data Science in Post-Covid Era

Data science has been the fastest-growing field in the last decade. But COVID 19 has forced us to put a hold on everything. Right now, all of us are sitting in our homes and expecting COVID-19 vaccine to arrive so life can return to normal. But will that normal be the same or will it deviate? And if it is a new normal, then, how will the analytics industry respond to the change?

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