How to Use TensorFlow in Python: Google‘s Open-Source Library For Deep Learning

You might not always know it, but Deep Learning is everywhere. Thanks to an advance in resources, both computationally and data-wise, the past years have seen an explosion in applications based on this Machine Learning technique. In this article, we introduce you to TensorFlow, Google‘s popular Deep Learning framework.

Some knowledge of Python and the basics of Machine Learning will help to understand the examples. If you feel that your Python foundations are still a bit shaky, you might want to check out our Introduction to Programming. Are you ready? Let‘s get started.

What Is Deep Learning?

Deep Learning is a type of Machine Learning. The models in this field are conceptualized as graphs that consist of interconnected layers. Most of these layers are “hidden,” meaning that we cannot directly observe their in- and output.

In such a graph, information is transported and transformed by mimicking the neuronal processes in the brain. It is for this reason that these deep models are referred to as artificial neural networks.

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top 30 Python Tips and Tricks for Beginners

Welcome to my Blog , In this article, you are going to learn the top 10 python tips and tricks.

1) swap two numbers.

2) Reversing a string in Python.

3) Create a single string from all the elements in list.

4) Chaining Of Comparison Operators.

5) Print The File Path Of Imported Modules.

6) Return Multiple Values From Functions.

7) Find The Most Frequent Value In A List.

8) Check The Memory Usage Of An Object.

…

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Python Packages in SQL Server – Get Started with SQL Server Machine Learning Services

Introduction

When installing Machine Learning Services in SQL Server by default few Python Packages are installed. In this article, we will have a look on how to get those installed python package information.

Python Packages

When we choose Python as Machine Learning Service during installation, the following packages are installed in SQL Server,

• revoscalepy – This Microsoft Python package is used for remote compute contexts, streaming, parallel execution of rx functions for data import and transformation, modeling, visualization, and analysis.
• microsoftml – This is another Microsoft Python package which adds machine learning algorithms in Python.
• Anaconda 4.2 – Anaconda is an opensource Python package

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Google's TPU's being primed for the Quantum Jump

The liquid-cooled Tensor Processing Units, built to slot into server racks, can deliver up to 100 petaflops of compute.

The liquid-cooled Tensor Processing Units, built to slot into server racks, can deliver up to 100 petaflops of compute.

As the world is gearing towards more automation and AI, the need for quantum computing has also grown exponentially. Quantum computing lies at the intersection of quantum physics and high-end computer technology, and in more than one way, hold the key to our AI-driven future.

Quantum computing requires state-of-the-art tools to perform high-end computing. This is where TPUs come in handy. TPUs or Tensor Processing Units are custom-built ASICs (Application Specific Integrated Circuits) to execute machine learning tasks efficiently. TPUs are specific hardware developed by Google for neural network machine learning, specially customised to Google’s Machine Learning software, Tensorflow.

The liquid-cooled Tensor Processing units, built to slot into server racks, can deliver up to 100 petaflops of compute. It powers Google products like Google Search, Gmail, Google Photos and Google Cloud AI APIs.

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Reflecting On My First 5 Months As An Open-Source Contributor

Hey there everybody,

Early in 2020 I started a journey as a Content Creator, where I’ve been writing technical content on Software Development — mostly focused on the Python stack.

In the past 5 months, I began a new journey as an open-source contributor, and to date, I’ve contributed to 8 different python packages.

I’m going to share my story as 5-month old contributor with you here, along with my thoughts on why it’s beneficial to contribute to open source.

This article originally started as a thread on Twitter and then decided to turn it into an article regarding my journey as an open-source contributor. I hope you’ll enjoy it, and take your time!

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