Apache Spark™ is a unified analytics engine for large-scale data processing. Apache Spark is a fast and general-purpose cluster computing system. It provides high-level APIs in Java, Scala, Python and R, and an optimized engine that supports general execution graphs. It … Continue reading detecting fraud with decision tree and spark
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
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
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.
We have discussed that an image is nothing but a logical array with number in each pixel representing the intensity of light in each pixel . And we can think it as numpy array and to work with it we … Continue reading Drawing With OpenCV
An image, digital image, or still image is a binary representation of visual information, such as drawings, pictures, graphs, logos, or individual video frames. Digital images can be saved electronically on any storage device. Objectives: In this post we are going to analysis the building blocks of an … Continue reading A Constructive Analysis Of Image Data
Computer vision is an interdisciplinary scientific field that deals with how computers can be made to gain high-level understanding from digital images or videos. From the perspective of engineering, it seeks to automate tasks that the human visual system can do. what computer vision consist of : Artificial intelligence: Areas of artificial intelligence deal with autonomous planning or deliberation for robotical systems to navigate through an environment. A detailed understanding of these environments is required to navigate through them. Information about the environment could be provided by a computer vision system, acting as a vision sensor and providing high-level information about the environment and the robot. Artificial intelligence … Continue reading What is Computer Vision An Introduction
Ceiling Analysis is a way to systematically find the weakest component of your system, and therefore optimising that weakest component would best serve your time to bring the greatest improvement to the overall system. Why it is important in case of deep learning? Ceiling analysis is the process of manually overriding each component in your system to provide 100% accurate predictions with that component. Thereafter, you can observe the overall improvement of your deep learning system component by component. For photo OCR example, this is what we might have: Component Accuracy Note Overall system 72% Text Detection (TD) 89% Make … Continue reading Ceiling Analysis in Machine Learning?
This post is inspired by Andrew Ng’s deep learning specialization so if you are really interested in this project do check the course. So here comes the questions why ML stratergy? well the answer can be pretty motivating suppose you … Continue reading ML Strategy for Machine Learning Projects
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