Imagine you’re working as an intern in a company, and you use your personal account for creating dashboards on Data Studio. One day, your boss asks you to transfer everything you’ve made to the company’s account, i.e., make their account as the owner of dashboards so that when you leave, your work doesn’t.

1. Report: Your visualization.
2. Data Source: The data embedded in your visualization. With this, you can change the schema of your report by adding calculated fields, filters, etc.
3. Dataset: The data you want to visualize.
4. Connector: Platform you use to fetch your data. Here, we…

Many beginners of Machine Learning prefer starting with the scikit-learn library, no exception in my case either. But they tend to forget the importance of building models from scratch. Starting from scratch gives you the real answers. How to multiply the weights and features? What about the bias? In fact, what is bias? How to perform the sigmoid function? How to calculate the Loss? How to find the optimized values of weights? If you’ve had these questions then you’re on the right track, bud! And it’s time to start from scratch!

So, one of the most prominent tools you’ll…

So anyone here who is beginning with Anaconda that too on Windows, You have got to thank the developers of it first, because us Windows people aren’t as blessed as ‘Linux-based OS’ people (Please don’t send a link to how to dual boot Ubuntu with Windows 10). If you know, you know.

And if you don’t know, here’s why:

Linux supports almost all of the programming languages such as Java, Python, Julia, Ruby, C, and C++ to name a few, by default.

‘Linux-based OS’ people know what it feels like to have everything at one place. …

Namrata Tanwani

Curious. Curious about data, curious about its science, curious about why my dog doesn’t love me back. Usually found listening to stories humans share.

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