Deep Learning Regression with Python

Learn deep learning regression from basic to expert level through a practical course with Python programming language.

Learn deep learning regression through a practical course with Python programming language using S&P 500® Index ETF prices historical data for algorithm learning. It explores main concepts from basic to expert level which can help you achieve better grades, develop your academic career, apply your knowledge at work or do your business forecasting research. All of this while exploring the wisdom of best academics and practitioners in the field.

Become a Deep Learning Regression Expert in this Practical Course with Python

  • Read or download S&P 500® Index ETF prices data and perform deep learning regression operations by installing related packages and running code on Python IDE.
  • Create target and predictor algorithm features for supervised regression learning task.
  • Select relevant predictor features subset through Student t-test and ANOVA F-test univariate filter methods and extract predictor features transformations through principal component analysis.
  • Train algorithm for mapping optimal relationship between target and predictor features through artificial neural network, deep neural network and recurrent neural network.
  • Regularize algorithm learning through nodes connections weight decay, visible or hidden layers dropout fractions and stochastic gradient descent algorithm learning rate.
  • Extract algorithm predictor features through stacked autoencoder.
  • Minimize recurrent neural network vanishing gradient problem through long short-term memory units.
  • Test algorithm for evaluating previously optimized relationship forecasting accuracy through scale-dependent metrics.
  • Assess mean absolute error, mean squared error and root mean squared error scale-dependent metrics.

Become a Deep Learning Regression Expert and Put Your Knowledge in Practice

Learning deep learning regression is indispensable for data mining applications in areas such as consumer analytics, finance, banking, health care, science, e-commerce and social media. It is also essential for academic careers in data mining, applied statistical learning or artificial intelligence. And its necessary for business forecasting research.

But as learning curve can become steep as complexity grows, this course helps by leading you step by step using S&P 500® Index ETF prices historical data for algorithm learning to achieve greater effectiveness.

Your Instructor


Hi! We are UpDegree, providing high quality interactive course.

We are the team of 100+ instructor over the globe. Adel (Oxford), Anand (Standford), Akash (IITB), Rajib (IITK), Partha (IITM) are few of them.

Updegree courses are different, In each and every course you not only get the videos lectures but you also get quiz,code,assignment etc to test your practical understanding!

Frequently Asked Questions

When does the course start and finish?
The course starts now and never ends! It is a completely self-paced online course - you decide when you start and when you finish.
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How does lifetime access sound? After enrolling, you have unlimited access to this course for as long as you like - across any and all devices you own.
What if I am unhappy with the course?
We would never want you to be unhappy! If you are unsatisfied with your purchase, contact us in the first 30 days and we will give you a full refund.

This course is closed for enrollment.