Agile Methodology For data scientist?

What is Agile Methodology? AGILE methodology is a practice that promotes continuous iteration of development and testing throughout the software development lifecycle of the project. Both development and testing activities are concurrent unlike the Waterfall model. The agile software development emphasizes on four core values. Individual and team interactions over processes and tools Working software over comprehensive…

The Basics of Bayesian Statistics

Bayesian statistics mostly involves conditional probability, which is the the probability of an event A given event B, and it can be calculated using the Bayes rule. The concept of conditional probability is widely used in medical testing, in which false positives and false negatives may occur. A false positive can be defined as a positive outcome on…

Markov Chains

A popular model for systems that change over time in a random manner is theMarkov chain model. A Markov chain is a sequence of random variables, one foreach time. At each time, the corresponding random variable gives the state of thesystem. Also, the conditional distribution of each future state given the past statesand the present…

Understanding Joins

Join Fundamentals By using joins, you can retrieve data from two or more tables based on logical relationships between the tables. Joins indicate how SQL Server should use data from one table to select the rows in another table. A join condition defines the way two tables are related in a query by: Specifying the…

Using Tensorflow estimator API to not write Boilerplate codes

What we are doing here : predicting price of taxifare dataset. We are using tensorflow and the high level estimator API . As we know machine learning is a very buzz words now a days and we strongly believe that everyone should needs to know the nuts and and bolts of machine learning so without…

Azure Machine Learning

A workspace is a context for the experiments, data, compute targets, and other assets associated with a machine learning workload. Workspaces for Machine Learning Assets A workspace defines the boundary for a set of related machine learning assets. You can use workspaces to group machine learning assets based on projects, deployment environments (for example, test…

Azure SQL Database to store App data

Managing data is a critical component of any business. Relational databases, and specifically Microsoft SQL Server, have been among the most common tools for handling that data for decades. If we want to manage our data using the cloud, we can just use Azure virtual machines to host our own Microsoft SQL Server instances. Sometimes that’s the…

Understand The Service Azure Provides for Data Engineers

Even the most experienced data engineer can feel overwhelmed by the range of data platform technologies in Microsoft Azure. In diverse scenarios and industries, data engineers must solve complex data problems to provide business value through data. By understanding the data types and capabilities of the data platform technologies, a data engineer can pick the…

Data Mining Concepts in SQL SERVER 2014

Data mining is the process of discovering actionable information from large sets of data. Data mining uses mathematical analysis to derive patterns and trends that exist in data. Typically, these patterns cannot be discovered by traditional data exploration because the relationships are too complex or because there is too much data. These patterns and trends…

Learn Git In Simple Way

To check whether you have git install in your device in your terminal type git –version let’s talk about git init command in details. The git init command creates a new Git repository. It can be used to convert an existing, un- versioned project to a Git repository or initialize a new, empty repository. Most other Git…

Let’s Excel

SCENARIO VanArsdel is a company that manufactures and sells sporting goods. The company has offices in the United States (US) and several other countries. Its sales comprise of US sales and International sales. VanArsdel’s sales come from its owned manufactured products, as well as other manufacturers’ products.  Bobby is a district manager who is responsible for several…

Creating Mash-ups of data from multiple source in Excel

VanArsdel is a company that manufactures and sells sporting goods. The company has offices in the United States (US) and several other countries. Its sales comprise of US sales and International sales. VanArsdel’s sales come from its owned manufactured products, as well as other manufacturers’ products.  VanArsdel’s US office stores the sales data on a SQL…

Explore the Excel Data Model

Download and open file You should see a blank worksheet when opening the file. Open the Data Model by selecting the Manage Data Model icon from either the Data or PowerPivot tabs in Excel 2016; from the PowerPivot tab in Excel 2013; or the Power Pivot Window icon from the PowerPivot tab in Excel 2010.The…

Explore the Classic Excel Dashboard

Problem: VanArsdel is a company that manufactures and sells sporting goods. The company has offices in the United States (US) and several other countries. Its sales comprise of US sales and International sales. VanArsdel’s sales come from its owned manufactured products, as well as other manufacturers’ products. VanArsdel’s Canada’s office has sent you their sales…

Create your first Cloud Pub/Sub topic

A Cloud Pub/Sub topic is a named resource to which devices send messages. Create your first topic with the following command: gcloud pubsub topics create my-topic You will send several messages to this topic later. Create a subscription to the device’s topic Run the following command to create a subscription, which allows you to view the messages…

An Introduction to Cloud Composer

Workflows are a common theme in data analytics – they involve ingesting, transforming, and analyzing data to figure out the meaningful information within. In Google Cloud Platform (GCP), the tool for hosting workflows is Cloud Composer which is a hosted version of the popular open source workflow tool Apache Airflow. Setup and requirements log in…

What Is Federated Learning?

Standard machine learning approaches require centralizing the training data on one machine or in a datacenter. And Google has built one of the most secure and robust cloud infrastructures for processing this data to make our services better. Now for models trained from user interaction with mobile devices, we’re introducing an additional approach: Federated Learning. Federated…

Predict prices using regression with ML.NET

You can follow along or download the source code here. 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,…

Create an IoT hub using the Azure portal

Create an IoT hub This section describes how to create an IoT hub using the Azure portal. Sign in to the Azure portal. From the Azure homepage, select the + Create a resource button, and then enter IoT Hub in the Search the Marketplace field. Select IoT Hub from the search results, and then select Create. On the Basics tab, complete the fields as follows: Subscription: Select the…

Deploy and run an IoT device simulation in Azure

Deploy Device Simulation When you deploy Device Simulation to your Azure subscription, you must set some configuration options. Sign in to azureiotsolutions.com using your Azure account credentials. Click the Device Simulation tile: Click Try now on the Device Simulation description page: On the Create Device Simulation solution page, enter a unique Solution name. Select the Subscription and Region you want to use to deploy the solution accelerator. Typically,…

How Azure Machine Learning works: Architecture and concepts

How Azure Machine Learning works: Architecture and concepts Register for Upcoming event and send us a mail: Workflow The machine learning model workflow generally follows this sequence: Train Develop machine learning training scripts in Python or with the visual designer. Create and configure a compute target. Submit the scripts to the configured compute target to run in that environment….

Introduction Into Azure Machine Learning

Azure Machine Learning is a platform for operating machine learning workloads in the cloud. Built on the Microsoft Azure cloud platform, Azure Machine Learning enables you to manage: Scalable on-demand compute for machine learning workloads. Data storage and connectivity to ingest data from a wide range sources. Machine learning workflow orchestration to automate model training,…

Deploy a machine learning model with the designer

Create a real-time inference pipeline To deploy your pipeline, you must first convert the training pipeline into a real-time inference pipeline. This process removes training modules and adds web service inputs and outputs to handle requests. Create a real-time inference pipeline Above the pipeline canvas, select Create inference pipeline > Real-time inference pipeline.Your pipeline should now look like…

Predict automobile price with the designer: A regression problem

Create a new pipeline Azure Machine Learning pipelines organize multiple machine learning and data processing steps into a single resource. Pipelines let you organize, manage, and reuse complex machine learning workflows across projects and users. To create an Azure Machine Learning pipeline, you need an Azure Machine Learning workspace. In this section, you learn how…

What is Azure Machine Learning?

Azure Machine Learning can be used for any kind of machine learning, from classical ml to deep learning, supervised, and unsupervised learning. Whether you prefer to write Python or R code or zero-code/low-code options. Start training on your local machine and then scale out to the cloud. The service also interoperates with popular open-source tools,…

MLOps: Model management, deployment and monitoring with Azure Machine Learning

learn how to use Azure Machine Learning to manage the lifecycle of your models. Azure Machine Learning uses a Machine Learning Operations (MLOps) approach. MLOps improves the quality and consistency of your machine learning solutions. Azure Machine Learning provides the following MLOps capabilities: Create reproducible ML pipelines. Pipelines allow you to define repeatable and reusable…

Monitor SQL performance in Linux

When you run SQL Server 2017 on a Linux server, you cannot use Windows Performance Monitor to gather and display performance counters because Performance Monitor is not supported on Linux. Suppose you are a database administrator for a global novelty goods importer called Weed World Importers. You have migrated your customer-facing product database to a…

Classify Images of Clouds in the Cloud with AutoML Vision

AutoML Vision helps developers with limited ML expertise train high quality image recognition models. Once you upload images to the AutoML UI, you can train a model that will be immediately available on GCP for generating predictions via an easy to use REST API. In this lab you will upload images to Cloud Storage and…

Machine Learning with Spark on Google Cloud Dataproc

In this post you will learn how to implement logistic regression using a machine learning library for Apache Spark running on a Google Cloud Dataproc cluster to develop a model for data from a multivariable dataset. Google Cloud Dataproc is a fast, easy-to-use, fully-managed cloud service for running Apache Spark and Apache Hadoop clusters in a…

Azure Platform for Data Engineers(part-2)

Explore data types: Azure provides many data platform technologies to meet the needs of common data varieties. It’s worth reminding ourselves of the two broad types of data: structured data and nonstructured data. Structured data In relational database systems like Microsoft SQL Server, Azure SQL Database, and Azure SQL Data Warehouse, data structure is defined…

Azure Platform for Data Engineers(part-1)

Over the last 30 years, we’ve seen an exponential increase in the number of devices and software that generate data to meet current business and user needs. Businesses store, interpret, manage, transform, process, aggregate, and report this data to interested parties. These parties include internal management, investors, business partners, regulators, and consumers. Data consumers view…

Cloud Engineering: Creating a Virtual Machine

Introduction: Google Compute Engine lets you create virtual machines running different operating systems, including multiple flavors of Linux (Debian, Ubuntu, Suse, Red Hat, CoreOS) and Windows Server, on Google infrastructure. You can run thousands of virtual CPUs on a system that has been designed to be fast and to offer strong consistency of performance. Here,…

Get To Know About Big Data Analytics

Storing and Accessing Data, Comparison An RDBMS system keeps your table definitions (that is, the schema) in a data dictionary, which is tightly coupled with your tables: it’s always kept in exact alignment, accurately describing the tables you create. This tight coupling also means that the schema governs what is allowed to be stored as data. These systems are…

How to Use AutoML and Vision API in GCP

What is the Vision API and what can it do? The vision API is an API that uses machine learning and other Google services to extract information from images. The sorts of predictions that it can currently make include but are not limited to the following list: Label Detection, which is used to detect the…

Developers Guide into Neo4j(present and future of database)

As a developer, you will create Neo4j Databases, add and update data in them, and query the data. When you learn to use Neo4j as a developer, you have three options⎼ Neo4j Desktop, Neo4j Aura, or Neo4j Sandbox. In this module you will learn how to use each of these development environments and select the…

insights from E-Commerce retail data set

We are using Bigquery as our data warehouse solution and using standard SQL as query language . For dataset we use Google’s Google Analytics logs of an merchants website. You need to enable your bigquery account which has a daily limit and there after it is cost effective. Click Navigation menu > BigQuery. Click Done. BigQuery public datasets are…

BigQuery ML(move your model towards data and not data towards model)

Overview BigQuery ML enables users to create and execute machine learning models in BigQuery using standard SQL queries. BigQuery ML democratizes machine learning by enabling SQL practitioners to build models using existing SQL tools and skills. BigQuery ML increases development speed by eliminating the need to move data. BigQuery ML functionality is available by using:…

.Net framework and Apache spark

Why choose .NET for Apache Spark? .NET for Apache Spark empowers developers with .NET experience or code bases to participate in the world of big data analytics. .NET for Apache Spark provides high performance APIs for using Spark from C# and F#. With C# and F#, you can access: DataFrame and SparkSQL for working with…

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…

What is quantum computing?

There are some problems so difficult, so incredibly vast, that even if every supercomputer in the world worked on the problem, it would still take longer than the lifetime of the universe to solve. Quantum computers hold the promise to solve some of our planet’s biggest challenges – in environment, agriculture, health, energy, climate, materials…

How to use Cloud Storage and Cloud SQL

In this post, you create a Cloud Storage bucket and place an image in it. You’ll also configure an application running in Compute Engine to use a database managed by Cloud SQL. For this lab, you will configure a web server with PHP, a web development environment that is the basis for popular blogging software….

Use Of Cloud IoT Core

Use IoT Core to create a registry Use IoT Core to create a device Use Stackdriver Logging to view device logs Enable APIs In this section, you check that all the APIs you will use in this lab are enabled. In the GCP Console, on the Navigation menu (), click APIs & Services. Scroll down and confirm that…

Using Pubsub to publish messages

Google Cloud Pub/Sub is a messaging service for exchanging event data among applications and services. A producer of data publishes messages to a Cloud Pub/Sub topic. A consumer creates a subscription to that topic. Subscribers either pull messages from a subscription or are configured as webhooks for push subscriptions. Every subscriber must acknowledge each message…

IOT Sensors and connections

A sensor is a module that observes changes in its environment and sends information about these changes to a device. Devices collect data from sensors and send it to the cloud. Devices can be very small and have very few resources in terms of compute, storage, and so on. They might be able to communicate…

IOT in GCP

Security is critical when deploying and managing an IoT network. Cloud IoT Core has several security features to protect your IoT network. Devices are authenticated individually. Which means if there is an attack on your IoT network it is limited to one device and not the whole fleet. There are four public key formats available…