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Analyzing logs in real time using Fluentd and BigQuery

This tutorial shows how to log browser traffic and analyze it in real time. This is useful when you have a significant amount of logging from various sources and you want to debug issues or generate up-to-date statistics from the logs. The tutorial describes how to send log information generated by an NGINX web server to BigQuery using Fluentd, and then use BigQuery to analyze the log information. It assumes that you have basic familiarity with Google Cloud Platform (GCP), Linux command lines, application log collection, and log analysis. Introduction Logs are a powerful tool for providing a view into how large-scale … Continue reading Analyzing logs in real time using Fluentd and BigQuery

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Machine Learning crash course (Tensorflow Examples)

machine learning comes with the learning pattern which is supervised learning at a first glance .so here is a brief about it terms used here are : the very first thing needs to keep in mind is framing your machine learning model/projects means what you want to achieve out of the data. example may contains as follows: A regression model predicts continuous values. For example, regression models make predictions that answer questions like the following: What is the value of a house in California? What is the probability that a user will click on this ad? A classification model predicts discrete values. For example, … Continue reading Machine Learning crash course (Tensorflow Examples)

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Analyzing Financial Time Series Using BigQuery and Cloud Datalab

This solution illustrates the power and utility of BigQuery and Cloud Datalab as tools for quantitative analysis. The solution provides an introduction (this document) and gets you set up to run a notebook-based Cloud Datalab tutorial. If you’re a quantitative analyst, you use a … Continue reading Analyzing Financial Time Series Using BigQuery and Cloud Datalab

Running Spark on Azure Databricks

Who Should See This Blog Post? This course is intended for the people who wants to Run their Analytics workload and Machine Learning workload on DataBricks And chosen Azure as their distributor. Skills Required To Follow: SQL Machine Learning Why we need DataBricks and Azure services ….. well we can train one model on DataBricks and deploy it on Azure Services Before we can run a spark job we needs to create a computer cluster and before we create a computer cluster we need to create a DataBricks Workspace.All the work done in DataBricks need not to be done within … Continue reading Running Spark on Azure Databricks

A Practical Approach To Stochastic gradient descent(SGD)

Stochastic gradient descent (often abbreviated SGD) is an iterative method for optimizing an objective function with suitable smoothness properties (e.g. differentiable or subdifferentiable). It is called stochastic because the method uses randomly selected (or shuffled) samples to evaluate the gradients, hence SGD can be regarded as a stochastic approximation of gradient descent optimization. Background Both statistical estimation and machine learning consider the … Continue reading A Practical Approach To Stochastic gradient descent(SGD)

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Machine Learning Applications for Big Data(Regression):

Machine Learning: Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. Machine learning focuses on the development of computer programs that can access data and use it … Continue reading Machine Learning Applications for Big Data(Regression):

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