Techtalks: Data Science

I have a Keras ML model .h5 file that I would like to publish as a web service. This model was created in Databricks. I want to use Azure ML for this purpose. I am following the steps given in this Azure documentation.

One of the prerequisites is to have "Azure Machine Learning SDK". All these topics are discussed in the Ai ml Certification.

My question is how to install "Azure Machine Learning SDK" in my Azure ml workspace. Do I need to type the commands in the Cloud Shell?

Any pointers would be helpful. Thanks.

In Tableau, the notation "[62:33]" in the error message is used to indicate the specific location within your Custom SQL Query where the error occurred. It provides a way to pinpoint the line and character position in your query where Tableau encountered a problem. Here's how to interpret it:

• 62: This number represents the line number in your Custom SQL Query where the error occurred. In this case, the error is on line 62 of your query.

• 33: This number represents the character position within line 62 where the error was encountered. It indicates that the issue occurred 33 characters into line 62.

So, in your specific error message, Tableau is telling you that there's an issue related to the "Field1" name being ambiguous, and it's located at line 62, character position 33 in your Custom SQL Query.

To track down the error and resolve it, you'll want to go to line 62 in your SQL query and review the code around character position 33. The ambiguity in the "Field1" name likely means that Tableau is having trouble determining which table or data source "Field1" is referring to within your query. You might need to provide more specific table aliases or adjust your query to make it unambiguous.

Hy Guys,

CCSP Course

With the help of this CCSP online training certification course, develop your knowledge of cloud security architecture, design, applications, and operations. You will get step-by-step instructions and a comprehensive lesson plan that is simple to follow covering every aspect of the CCSP, which will help you further your career in the expanding sector of cloud security.

The cost of Robotic Process Automation (RPA) certification can vary widely depending on several factors, including the certification provider, the level of certification, and your location. Here are some general guidelines:

• Certification Provider: Different organizations and vendors offer RPA certifications. Some of the popular ones include UiPath, Blue Prism, Automation Anywhere, and Microsoft. Each of these providers may have their own pricing structure for certification exams and training materials.
• Certification Level: RPA certifications often come in different levels, such as beginner, intermediate, and advanced. The cost of certification may increase with the level of expertise being tested. For example, an entry-level certification might be less expensive than an advanced certification.
• Training Materials: In addition to the exam fee, you may need to invest in training materials, courses, and study resources to prepare for the certification. These additional costs can vary depending on the provider and your chosen method of study.
• Location: The cost of certification exams can also vary by region. Some regions may have lower or higher exam fees based on local market conditions.
• Promotions and Discounts: Some certification providers offer promotions, discounts, or bundle deals that can reduce the overall cost of certification.

To get the most accurate and up-to-date information on the cost of RPA certification, it's recommended to visit the official website of the certification provider you're interested in or contact their customer support. They will provide you with specific pricing details for the certification program you wish to pursue. Additionally, you can check if there are any community colleges, universities, or online platforms that offer RPA courses and certification at a lower cost compared to vendor-specific certifications.

Hello

Thanks Zaid md,

Data profiling in ETL is the process of analyzing and assessing the quality and structure of source data before it is loaded into a data warehouse or repository. The purpose is to identify potential data quality issues, define rules and transformations, and ensure the accuracy, completeness, and consistency of the data. By performing data profiling, organizations can make informed business decisions and improve the overall quality of their data. salesforce field service lightning certification

Yes, there are several free and open source image recognition APIs available:

Clarifai - An open source image and video recognition API. It has a generous free tier.

Amazon Rekognition - Amazon's image and video analysis service. Has a free tier that offers 5,000 transactions per month.

Microsoft Computer Vision - Provides image analysis and description. The free tier offers 5,000 transactions per month.

Google Cloud Vision API - Google's image recognition service. The free tier offers 1,000 requests per month.

OpenCV - A popular computer vision and machine learning software library. Can be used to build custom image recognition models and applications.

Tensorflow/Keras - Deep learning frameworks that can be used with transfer learning to build image classifiers. Free to use and open source.

IBM Watson Visual Recognition - IBM's visual recognition service. The free tier offers 50 API calls per month.

Alteryx Computer Vision - A library of computer vision tools for tasks like object detection, image classification etc. Open source.

DeepDetect - A framework for deep learning microservices including image recognition. Free for non-commercial use.

Cloudsight - Provides image recognition via a REST API. The free tier allows 1,000 API calls per month. 

So in summary, Clarifai, Amazon Rekognition, OpenCV and libraries like Tensorflow offer the most full-featured free open source options.

Relational Database (RDBMS)

• RDBMS is a DBMS that enables the organization of aggregated data.
• Relational DBMS is the most widely used database like Oracle, SQL Server. It is characterized by handling data in tables with basic keys that make it possible to identify the rows in each table separately. And an external key that allows you to associate the table with other tables.

OLAP (Online Analytical Processing)

• OLAP is a collection of software tools that provide information to business decision-makers.
• OLAP usually works on a standardized database to facilitate OLAP, not OLTP. These databases are often referred to as data warehouses.
• You can check the comparison and key differences between OLAP vs OLTP here