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Recommend Products using ML with Cloud SQL and Dataproc

As our goal is to provide demo that is why we are using the Cloud SQL or else yo can use spanner for horizontal scaling. our goal is to Create Cloud SQL instance Create database tables by importing .sql files from Cloud Storage Populate the tables by importing .csv files from Cloud Storage Allow access to Cloud SQL Explore the rentals data using SQL statements from CloudShell  the GCP console opens in this tab.Note: You can view the menu with a list of GCP Products and Services by clicking the Navigation menu at the top-left, next to “Google Cloud Platform”.  you populate rentals … Continue reading Recommend Products using ML with Cloud SQL and Dataproc

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Dimensionality reduction using sklearn a way of reducing burden

Principal component analysis (PCA): PCA is used to decompose a multivariate dataset in a set of successive orthogonal components that explain a maximum amount of the variance. In scikit-learn, PCA is implemented as a transformer object that learns n components in its fit method, and can be used on new data to project it on these components. PCA centers but does not scale the input data for each feature before applying the SVD. The optional parameter parameter whiten=True makes it possible to project the data onto the singular space while scaling each component to unit variance. The PCA object also provides a probabilistic interpretation of the PCA that can give a likelihood … Continue reading Dimensionality reduction using sklearn a way of reducing burden

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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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Build A Tool in the Google docs that read the sentiment of your document by using Google’s Natural Language API

The Natural Language API is a pretrained machine learning model that can analyze syntax, extract entities, and evaluate the sentiment of text. It can be called from Google Docs to perform all of these functions. This post will walk you through calling the Natural Language API to recognize the sentiment of selected text in a Google Doc and highlight it based on that sentiment. What are we going to be building? Once this post is complete, you will be able to select text in a document and mark its sentiment, using a menu choice, as shown below. Text will be highlighted in … Continue reading Build A Tool in the Google docs that read the sentiment of your document by using Google’s Natural Language API

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Build simple Apps that can convert text-to-speech and speech-to-text but in c#

As a developer back in 2017 I always wonder it will be nice to write Machine learning code in c# .Net framework to show my manager that i know enough to become Team Lead but past is past and i left that productive company most of the company manager’s in the world are same full with dull insights as they tries to bring people down and demotivate them from their goal as they didn’t get their anyways the other day i was searching memes in the internet and all of a sudden one of the website gives me two HD … Continue reading Build simple Apps that can convert text-to-speech and speech-to-text but in c#

Predict prices using regression with ML.NET

Create a console application Create a .NET Core Console Application called “TaxiFarePrediction”. Create a directory named Data in your project to store the data set and model files. Install the Microsoft.ML NuGet Package:In Solution Explorer, right-click the project and select Manage NuGet Packages. Choose “nuget.org” as the Package source, select the Browse tab, search for Microsoft.ML, select the package in the list, and select the Install button. Select the OK button on the Preview Changesdialog and then select the I Accept button on the License Acceptance dialog if you agree with the license terms for the packages listed. Do the same for the Microsoft.ML.FastTree Nuget package. Prepare and understand the data Download the taxi-fare-train.csv and the taxi-fare-test.csv data sets and save them to the Datafolder you’ve created … Continue reading Predict prices using regression with ML.NET

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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

When Mom can’t figure it out whether there is a cat or dog Data Raconteur son build a classifier for her mom.

Hi I am a student in XYZ school but don’t think me a kid I know pretty well Deep learning for starter I can tell you the difference between perceptron and Deep Neural Networks .I bet 40% of you even … Continue reading When Mom can’t figure it out whether there is a cat or dog Data Raconteur son build a classifier for her mom.