TetraNoodle Team
The history of data science, machine learning, and artificial Intelligence is long, but it s only recently that technology companies – both start–ups and tech giants across the globe have begun to get excited about it Why? Because now it works. With the arrival of cloud computing and multi–core machines – we have enough compute capacity at our disposal to churn large volumes of data and dig out the hidden patterns contained in these mountains of data.
This technology comes in handy, especially when handling Big Data. Today, companies collect and accumulate data at massive, unmanageable rates for website clicks, credit card transactions, GPS trails, social media interactions, and so on. And it is becoming a challenge to process all the valuable information and use it in a meaningful way. This is where machine learning algorithms come into the picture. These algorithms use all the collected past data to learn patterns and predict results or insights that help us make better decisions backed by actual analysis.
You may have experienced various examples of Machine Learning in your daily life (in some cases without even realizing it). Take for example
In all these examples, machine learning is used to build models from historical data, to forecast the future events with an acceptable level of reliability. This concept is known as Predictive analytics. To get more accuracy in the analysis, we can also combine machine learning with other techniques such as data mining or statistical modeling.
Instructor Details
Courses : 12
Specification: Machine Learning In The Cloud With Azure Machine Learning
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13 reviews for Machine Learning In The Cloud With Azure Machine Learning
Add a review
| Price | $14.99 |
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| Provider | |
| Duration | 3 hours |
| Year | 2019 |
| Level | Beginner |
| Language | English |
| Certificate | Yes |
| Quizzes | Yes |
$14.99
Danilo Slana –
A lot of overhead (introduction, description …) for a little real learning till section 3. But improves from section 3 on. Sections 3, 4 and 5 are really good. Please add 7 and 8 with a few more examples of algorithms and perhaps a connection to python or .net or visual studio real world example.
Raghavendra KS –
The training was short & sweet. It covered most of the basics. The course content was easy to understand. The examples used & the way it was explained made sense. I would like to see more examples & real world usages to be included in future such trainings. That would help immensely. Thanks.
E.manish kumar –
very good cource
Carlos Augusto Monteiro Oeiras –
Muito bom curso, boas explana es e objetivo o suficiente para o aprendizado ser fluido e transparente.
Verity Daniels –
Excellent course. Very interesting.
Edoardo –
Tiny course
Wil L –
not enough content not enough examples
Vaughan Castine –
Delved into the mechanics of how to use the Azure ML tools but didn’t help people understand how to select or tune ML models. Questions from students were brushed off with good idea or data science is an art… This just keeps the learning at a superficial level and does little to improve the student learning experience.
Vaishnav Rachuri –
The course content is good but please also provide some basic knowledge on the machine learning algorithms.
Haris Rehman –
It was a good introductory Course.
Sarjit Kaur –
Starting to understand machine learning : )
Usoroh Idemete –
This course took me from Zero to Hero. Just one part that I did not get the facilitator do in Azure ML Response service web App during deployment on Azure Portal. I will be really grateful if I can get contact to the team for clarity so I can have that sorted out.
Chandan Kodagana –
Course was informative, not sure how updated it is, the last updated is 2 years back. Reference material is not available.