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TensorFlow Machine Learning on the Amazon Deep Learning AMI

TensorFlow is a popular framework used for machine learning. The Amazon Deep Learning AMI comes bundled with everything you need to start using TensorFlow from development through to production. In this post, you will develop, visualize, serve, and consume a TensorFlow machine learning model using the Amazon Deep Learning AMI.  Objectives Upon completion of this post you will be able to: Create machine learning models in TensorFlow Visualize TensorFlow graphs and the learning process in TensorBoard Serve trained TensorFlow models with TensorFlow Serving Create clients that consume served TensorFlow models, all with the Amazon Deep Learning AMI Prerequisites You should be familiar … Continue reading TensorFlow Machine Learning on the Amazon Deep Learning AMI

Practical Aspects Of Testing and Debugging in Machine Learning

This post tries to give you a sense of humor on how to work with debugging when you are calling yourself a ML engineer or Data scientist. This post reduces your task as a ML Engineer and gives you the ability to implement the understanding of basic life’s rules which is go slow , grow more. What We Are Discussing Here? Once you had finished of framing your idea and wasted 3-4 months trying copy paste other’s work to gain your reputation in your organization when everything fails as your organazation has a unique collection of data though organization is … Continue reading Practical Aspects Of Testing and Debugging in Machine Learning

You Can Blend Apache Spark And Tensorflow To Build Potential Deep Learning Solutions

Before we Start our journey let’s explore what is spark and what is tensorflow and why we want them to be combined. Apache Spark™ is a unified analytics engine for large-scale data processing. Features: Speed: Run workloads 100x faster. Apache Spark achieves high performance for both batch and streaming data, using a state-of-the-art DAG scheduler, a query optimizer, and a physical execution engine.(DAG means ) Logistic regression in Hadoop and Spark Ease of Use: Write applications quickly in Java, Scala, Python, R, and SQL.Spark offers over 80 high-level operators that make it easy to build parallel apps. And you can use … Continue reading You Can Blend Apache Spark And Tensorflow To Build Potential Deep Learning Solutions

End To End Scalable Machine Learning Project On Google Cloud With Beautiful Front End with Big Data-I

As you Explore the dataset in the past post in this post our key focus will be building sample model to test our machine learning knowledge and in the last post we will build it in scale and deploy .If You have not read my previous post(this will hurt me ) you can read it here before continue to this one or recap it if you forget the dataset and aim of our project(not life). First we need to create our dataset for our sample model because if you remembered we have millions of rows that we can’t fit in … Continue reading End To End Scalable Machine Learning Project On Google Cloud With Beautiful Front End with Big Data-I

End To End Scalable Machine Learning Project On Google Cloud With Beautiful Front End with Big Data

As the title suggest we will be using Big data(structured) as our resource , We will use GCP as our platform and we will use python as our saviour and kubernete for deployment and Finally we will have a working Machine learning project of our own. Note: The code and concept is taken from Google cloud tutorial on coursera So with out further wasting your time let’s start: So why data science projects or ML model with Big data are different than what we used to build on our github to showcase its the memory ……got it again right memory … Continue reading End To End Scalable Machine Learning Project On Google Cloud With Beautiful Front End with Big Data