Talk to someone with programming skills and discuss any subject about deep learning with them so that you could quickly jump in as a newbie. Though some people figure out various libraries embedding math is used universally, you needn't understand the theory to implement deep learning tasks, I still recommend you learn some math knowledge like partial derivative. Some resources could give you a good starting point like Stanford's online course CS231n, Deep Learning at Oxford 2015and Andrew Ng's Coursera class. Also, some interesting online books like Neural Networks and Deep Learning could also give you an assistance to deep learning. Facilities and toolkits should also be available.
This course is the next logical step in my deep learning, data science, and machine learning series. I've done a lot of courses about deep learning, and I just released a course about unsupervised learning, where I talked about clustering and density estimation. So what do you get when you put these 2 together?
Advanced Data Mining Projects with R takes you one step ahead in understanding the most complex data mining algorithms and implementing them in the popular R language. Follow up to our course Data Mining Projects in R, this course will teach you how to build your own recommendation engine. You will also implement dimensionality reduction and use it to build a real-world project. Going ahead, you will be introduced to the concept of neural networks and learn how to apply them for predictions, classifications, and forecasting. Finally, you will implement ggplot2, plotly and aspects of geomapping to create your own data visualization projects.By the end of this course, you will be well-versed with all the advanced data mining techniques and how to implement them using R, in any real-world scenario.
Are You an Ecologist or Conservationist Interested in Learning GIS and Machine Learning in R? Then this course is for you! I will take you on an adventure into the amazing of field Machine Learning and GIS for ecological modelling. You will learn how to implement species distribution modelling/map suitable habitats for species in R. My name is MINERVA SINGH and i am an Oxford University MPhil (Geography and Environment) graduate. I finished a PhD at Cambridge University (Tropical Ecology and Conservation). I have several years of experience in analyzing real life spatial data from different sources and producing publications for international peer reviewed journals.
About this course: Welcome to Course 3 - Models & Frameworks to Support Sales Planning – In this course, you'll go through a conceptual approach to selling models and frameworks. As a primary learning outcome of this course, we emphasize the improvement in the analytical competencies and skills to develop sales planning and management. And the learning process goes through the application of the models and frameworks that contribute to supporting these processes. This course is aimed at professionals who seek improvement in conceptual support to the sales planning process, especially with an emphasis on applying selling models and frameworks methodology. At this point of the Strategic Sales Management specialization, you have an excellent understanding of the integration of sales planning to the strategy of the company.
Just to let you know, if you buy something featured here, Mashable might earn an affiliate commission. A partnership between Broadcom and the University of Cambridge, the U.K. based Raspberry Pi Foundation creates credit card-sized computers that promote learning how to code and educational research. Since the computers went on the market in 2012, Raspberry Pi has sold over eight million models and is the United Kingdom's best-selling computer. Setting up a Raspberry Pi is easy. Simply plug in a monitor, mouse, and keyboard, and install the computer.