R Deep Learning Essentials
Harness the ability to build algorithms for unsupervised data using deep learning concepts with R
Master the common problems faced such as overfitting of data, anomalous datasets, image recognition, and performance tuning while building the models
Build models relating to neural
Rates of Evolution: A Quantitative Synthesis
How fast is evolution, and why does it matter? The rate of evolution, and whether it is gradual or punctuated, is a hotly debated topic among biologists and paleontologists. This book compiles and compares examples of evolution from laboratory, field, and fossil record studies, analyzing them to extract their underlying rates. It concludes that...
The Complete Idiot's Guide to Statistics, 2nd Edition
Statistics, statistics everywhere, but not a single word can we understand! Actually,
understanding statistics is a critically important skill that we all need to have in this
day and age. Every day, we are inundated with data about politics, sports, business,
the stock market, health issues, financial matters, and many other topics.... Scientific Methods in Mobile Robotics: Quantitative Analysis of Agent Behaviour Mobile robots are widely applied in a range of applications from transportation, surveillance through to health care. In all these applications it is clearly important to be able to analyse and control the performance of the mobile robot and it is therefore surprising that formalised methods to achieve this are not readily available. This book...
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