Some tips on how to boost your public speaking skills as a data scientist — Data science is a relatively new field, and public speaking is an essential skill for anyone looking to build a career in this field. The ability to communicate complex data concepts clearly and effectively is essential for success in data science. If you’re data-driven and looking to boost your career…

Tips on what your Data Science career could look like — Data science has become one of the most in-demand fields in recent years. As companies increasingly collect and generate data, they need individuals who can sift through this information to identify trends and make predictions. While a data scientist’s job may vary depending on the industry, their responsibilities usually fall…

Which profile does your company need? A comparison between the two roles: skills, responsibilities, and their role in the team. — There’s a lot of debate in the tech world about whether data science managers or data science experts are more valuable to organizations. Some believe that managers are better able to develop and implement strategy, while others argue that experts are more skilled at working with data.

Successful data team: From who to hire first, to how to pick the next projects to work on — Working as a data scientist is one of the most in-demand jobs today. Companies are looking for data scientists to help them make better decisions, drive growth, and improve operational efficiency. But building a data science team from scratch can be a challenge. In this article, we’ll explore some tips…

A tutorial on how to build a dataset from scratch to give as input to a TensorFlow model. — TensorFlow is an open source, cross-platform library for Deep Learning built by Google. TensorFlow provides a way for developers to build artificial neural networks. …

What black points, lines, and areas represent in the graph produced by the plot() method defined by Prophet. — Prophet is a very popular algorithm for Time Series Analysis. You can create a new Prophet model very quickly, as shown in the following piece of code: from prophet import Prophet m = Prophet() m.fit(df) future = m.make_future_dataframe(periods=12) forecast = m.predict(future) where df is a Pandas dataframe.