1] What is the use of Hvantage Deep Learning and Machine Learning Toolkit?
Hvantage Deep Learning and Machine Learning Toolkit finds application in the creation of predictive applications. You can use the toolkit for building applications for flagging suspicious transactions, detecting fraudulent orders, forecasting demands, predicting user activities, filtering reviews, analyzing free texts, recommending items, and listening to social media feeds.
2] What are the benefits of Hvantage Deep Learning and Machine Learning Toolkit?
Hvantage offers Hvantage Deep Learning and Machine Learning Toolkit on AWS marketplace. With some of the major ML libraries including Panda, NLTK, Theano, Tensorflow, Torch, Gensim, Elastics, Spark, and CNTK, customers can reap the benefits of single-click server launch.
3] What is the Hvantage Support?
By launching an email helpdesk for Hvantage Deep Learning and Machine Learning Toolkit, Hvantage helps users solve issues while using and configuring ML libraries. We pride on our associations with efficient data scientists and ML experts, who will understand your problems and offer the perfect solutions to those issues. With in-depth knowledge of Python and ML algorithms, they can work on any predictive analysis issue.
4] What are the services offered by Hvantage Deep Learning and Machine Learning Toolkit?
The technology is designed for 24*7 availability. Users won't come across scheduled maintenance or downtimes. The evaluation, batch prediction, and model training API run on Amazon's secured, highly reliable, and proven data centers. Even if there's an 'availability zone outage' or 'server failure,' the toolkit will provide optimum fault tolerance with service-stack replications.
5] What are the charge's to launch Hvantage Deep Learning and Machine Learning Toolkit on AWS Cloud?
There are no charges involved in the process.
6] What is the Instance type for Hvantage Deep Learning and Machine Learning Toolkit on AWS Cloud?
It's T2 Medium with a storage capacity of 50GB.
7] What are the key features of the Toolkit?
Here are the essential features of this innovative toolkit:
- OS: Ubuntu 16.04 LTS
- Installed Libraries: Pandas, NLTK, Scikit-learn, Theano, TensorFlow, CAFFE, TORCH, Spark, Gensim, Elastics, CNTK.
- Python: - Python2/3
8] What are Hvantage Deep Learning and Machine Learning Toolkit and data science?
You want to draw conclusions from your data that help you solve a particular problem. The typical skills of a data scientists are
ML algorithms work on data models. It does not formulate manual rules but learns the entire data model. As a combination of computer science, mathematics, statistics, computational, and quantitative analyses, data science provides the impetus for better and improved decision making. ML or Machine Learning principles are integral parts of 'data science' projects. It finds application in the discovery of clustering algorithms and exploratory analysis. Data engineering happens to be a significant part of data science too, and it involves the collection, cleaning, and wrangling of crucial data sets. Data scientists will draw inferences from specific data sets that help them solve particular issues. The standard and common skills of data scientists include:
- Computer Science: Programming, hardware expertise
- Math: Calculus, Linear algebra, Statistics
- Communication: Presentation and Visualization
- Domain knowledge