How to prepare for Google Data Engineer Certification

Google’s data engineering certification is one of the new and emerging certifications in the industry right now for Data Engineering and Machine Learning. The exam will test on your ability to design, build and maintain data processing system and also analyze data, to gain insight into business outcomes and enable machine learning. I was able to pass the data engineer exam in Jan 2018. Through this blog, I would like to share my experience and the preparation guide, because at the time of writing I did not have enough materials to guide me on the exam.


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Would you survive the Titanic

We all know what happened on the Titanic. Spoiler Alert: Yes, Jack dies!


You may ask, do we need a machine learning to predict this? Even the next-door kid knows the answer. But jokes apart can we train a machine to predict who will survive the titanic crash? Continue reading “Would you survive the Titanic”

Building a simple Neural Network with Keras and Tensorflow

Neural networks have been a hot topic after the surfacing of deep learning. In these series of tutorials we will go in depth into building complex networks with Keras and Tensor Flow.


TensorFlow is an open-source library for machine learning introduced by Google. Keras provides a high level api/wrapper around TensorFlow.

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Linear Regression with pure Tensorflow

In this tutorial we will implement a simple linear regression with tensorflow. So what is linear regression ? In a nutshell it’s an efficient way to calculate the correlation between two variables. These two variables are identified as independent and dependent variables. We all use regression on an intuitive level every day. For this tutorial we can use real estate data(house area and price). Although real estate prices depends on all sort of variables for this example we assume that house prices increases with house area.


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