MACHINE LEARNING
Machine Learning For Data Analytics
INTRODUCTION
HOW DOES MACHINE LEARNING WORK?
TYPES OF MACHINE LEARNING
USES OF ML IN ANALYTICS
Identify patterns in data
Make predictions about future events
Cluster data into groups
Reduce the dimensionality of data
Improve the accuracy of data models
CHALLENGES OF ML IN ANALYTICS
It can be difficult to find and prepare the data that is needed to train the algorithms.
Machine Learning algorithms can be computationally expensive to train and run.
Some of the algorithms are difficult to interpret even though they work well.
FUTURE OF MACHINE LEARNING IN ANALYTICS
Machine learning is a rapidly evolving field, and there are many new developments in this area.
As machine learning algorithms become more powerful and efficient, they will be used for a wider range of data analytics tasks.
Machine learning will also be used to automate more tasks that are currently done manually.
0 notes
Hiring
Looking for building career in the most promissing profile?
We have it for you!
Apply for Business Analyst and Machine Learning Engineer role.
Get the best offer with the industry with us.
Hurry up, apply now!
Visit our website : https://marvel-inc.com/
0 notes
Sights and sounds from the recently concluded 2022 National conference of the Nigerian Society of Engineers NSE held at the international conference center Abuja. #nigeriasocietyofengineers #engineeringgals #womeninengineering #machinelearningengineer #pythonprogrammer #green #instaleadership #instatech #instatechnology #instamood (at International Conference Centre, Abuja) https://www.instagram.com/p/CmC3ltUNe7q/?igshid=NGJjMDIxMWI=
0 notes
Google Cloud Storage
The public cloud storage infrastructure for organisations known as Google Cloud Storage can be used to store big unstructured data volumes. Businesses may purchase the storage for crucial or infrequently used data.
Customers of Google Cloud Storage have the option of accessing their data through a web browser or a command-line interface. Customers can choose where their data will be stored as well.
Google Cloud Storage is a function of the Google Cloud Platform. It provides integrated object storage for both recent and old data. Buckets are used in Google Cloud Storage to organise stuff. Buckets are containers that can each have a specific storage class assigned to them in the cloud.
Google Cloud Storage provides four storage classes: Multi-Regional, Regional, Nearline, and Coldline. Pay-per-use, open authorization (OAuth), granular access controls, infinite data, the same tools and data access APIs across all classes, and access to additional Google Cloud Storage services are all features shared by all classes. All mentioned prices as of July 2017 reflect the most recent data.
Google Cloud Storage Multi-Regional
Data is stored in data centres all around the world and is made available with a 99.95% availability rate via Cloud Storage by Google Multi-Regional. It is suitable for companies that frequently need to access data, such as data for mobile applications and website content. Multi-Regional class data is stored in at least two different locations to increase availability. It costs $0.026 per gigabyte (GB) per month, depending on the region.
Google Cloud Storage Regional
Google Cloud Storage Regional stores data in a single location rather of distributing it among numerous. It ensures 99.9% availability and is the best choice for compute, analytics, and machine learning applications. When storage and processing resources are available in the same location, Google Cloud Storage Regional provides high performance and availability. Regional data storage is a technique for reducing network expenses. The monthly cost for local Google Cloud Storage is $0.02 per GB.
Google Cloud Storage Nearline
Google Cloud Storage Nearline is available to customers who need long-term storage for data that users access less than once per month. It connects with backup products from independent businesses like Unitrends and Symantec, and it functions best for data archiving, backup, and disaster recovery (DR).
For Google Cloud Storage Nearline, which touts 99% availability, a minimum storage period of 30 days is necessary. Customers must also pay a compulsory data retrieval fee of $0.01 per GB per month in addition to the monthly storage fee of $0.01 per GB.
Google Cloud Storage Coldline
Customers of Cloud Storage by Google can utilise Coldline to store data that they access less frequently than once per year. DR and archiving are its main uses. Although it costs the least of the three storage levels ($0.007 per GB per month), it has a 90-day minimum storage requirement and a $0.05 per GB data retrieval fee. Third-party backup and storage solutions from companies like Veritas, Egnyte, and NetApp can be integrated by customers with Coldline.
Data from Coldline and Nearline classes can be stored in multiregional and locally crafted buckets by businesses.
Lifecycle Rules in Google Cloud Storage
Lifecycle rules enable different aspects of an object's lifespan within a particular bucket to be handled. Rules may be activated by factors such as age, storage class, date, state, and version. If the requirements are met, objects may be removed or moved to another class of Google Cloud Storage. There are other services that provide object storage lifecycle management besides Google Cloud Storage. Both Amazon S3 and Microsoft Azure Blob Storage offer capabilities resembling object lifecycle management. The main differences usually have to do with the different storage class types and the optimal strategy to employ the lifecycle rule capabilities.
It's essential to understand how to use Lifecycle Rules, a powerful tool offered by Google Cloud Storage. Although Google Cloud Storage has a low cost per gigabyte, when used for huge amounts of data or in conjunction with multiple API operations, the cost can quickly rise. This typically happens as a result of improper configurations or a failure to make use of the built-in features.
0 notes
Hiring
Innovation is calling, don't be the left out!
Join us and be the part of changing world.
If you think you are the perfect match for joining us as a Machine Learning Engineer or Business Analyst, apply now.
Let our search end up with you.
Hurry up, Apply before it gets late.
Visit our website : https://marvel-inc.com/
0 notes
Become a Machine Learning will expert and learn about applications of Machine Learning in different fields such as health care, banking, telecommunication, and so on.
For more information visit on https://myitcertificate.com/courses.php?type=Machine%20Learning%20AI
0 notes