The ultimate guide to data science interviews. Developed by FAANG engineers, it covers Python, algorithms, ML concepts, and interview questions. Get interview-ready in just a few hours.

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This course will increase your skills to crack the data science or machine learning interview. You will cover all the most common data science and ML concepts coupled with relevant interview questions.
You will start by covering Python basics as well as the most widely used algorithms and data structures. From there, you will move on to more advanced topics like feature engineering, unsupervised learning, as well as neural networks and deep learning.
This course takes a non-traditional approach to interview prep, in that it focuses on data science fundamentals instead of open-ended questions.

In all, this course will get you ready for data science interviews. By the time you finish this course, you will have reviewed all the major concepts in data science and will have a good idea of what interview questions you can expect.

Data Science Interview Handbook

<h2>What is TensorFlow?
</h2>

Tensorflow is an end-to-end machine learning platform for creating and deploying industry-standard machine learning models. It was created by the Google Brain team. TensorFlow can train and run neural networks of different types. It supports a large number of architectures, which makes creating robust models.

TensorFlow is a popular library, comparable to PyTorch, CNTK (by Microsoft), and Apache MXNet.
 



<h2>How does it work?</h2>
TensorFlow allow users to create data flow graphs, which describe how the data moves with nodes in the graph. Each node in the graph represents a mathematical operation, and each is a tensor or multidimensional array. TensorFlow applications can run on CPUs and GPUs. The power of TensorFlow is that it can enable GPUs for faster training and prediction.



Introduction to a very useful Python deep learning library called TensorFlow which contains almost all major architectures that developers can use to train a deep learning model pipeline.


Are You Ready to Become a Data Scientist?

Python Basics

Python Libraries

More Data Science Tools

Data Structures and Algorithms - I

Data Structures and Algorithms - II

Statistics and Probability

Feature Engineering

Basics of Machine Learning

Regression

Classification

Unsupervised Learning

Advanced Topics in Machine Learning

Conclusion

TensorFlow

What is TensorFlow?

How does it work?