By selecting the 'Susbcribe & Save' option you are enrolling in an auto-renewing subscription of Zookal Study Premium. Cancel at anytime.
Auto-Renewal
Your Zookal Study Premium subscription will be renewed each month until you cancel. You consent to Zookal automatically charging your payment method on file $19.99 each month after 1st month free period until you cancel.
How to Cancel
You can cancel your subscription anytime by visiting Manage account page, clicking "Manage subscription" and completing the steps to cancel. Cancellations take effect at the end of the 1st month free period (if applicable) or at the end of the current billing cycle in which your request to cancel was received. Subscription fees are not refundable.
Zookal Study Premium Monthly Subscription Includes:
Ability to post up to ten (10) questions per month.
20% off your textbooks order and free standard shipping whenever you shop online at
textbooks.zookal.com.au
Unused monthly subscription benefits have no cash value, are not transferable, and expire at the end of each month. This means that subscription benefits do not roll over to or accumulate for use in subsequent months.
Payment Methods
Afterpay and Zip Pay will not be available for purchases with Zookal Study Premium subscription added to bag.
$1.00 preauthorisation
You may see a $1.00 preauthorisation by your bank which will disappear from your statement in a few business days..
Email communications
By adding Zookal Study Premium, you agree to receive email communications from Zookal.
Data Science, Algorithms, and Computational Statistics
Published
27th August 2019
Related course codes
Data Science, Algorithms, and Computational Statistics
This book describes in detail the fundamental mathematics and algorithms of machine learning (an example of artificial intelligence) and signal processing, two of the most important and exciting technologies in the modern information economy. Taking a gradual approach, it builds up concepts in a solid, step-by-step fashion so that the ideas and algorithms can be implemented in practical software applications. Digital signal processing (DSP)
is one of the 'foundational' engineering topics of the modern world, without which technologies such the mobile phone, television, CD and MP3 players, WiFi and radar, would not be possible. A relative
newcomer by comparison, statistical machine learning is the theoretical backbone of exciting technologies such as automatic techniques for car registration plate recognition, speech recognition, stock market prediction, defect detection on assembly lines, robot guidance, and autonomous car navigation. Statistical machine learning exploits the analogy between intelligent information processing in biological brains and sophisticated statistical modelling and inference. This book gives a solid
mathematical foundation to, and details the key concepts and algorithms in this important topic.