An Introduction to Statistical Learning: With Applications in R by Gareth JamesAn Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree- based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.
Growing up, my family was dysfunctional. I realize that this is redundant. No family system is completely healthy. There are always portions of the family that will be irresponsible. From this environment, I grew up, and I learned, imperfectly, how to find safe people — people who I could share my burdens with. See Choice Theory for more on our inner worlds. This requires discernment.
Healthy relationships are essential for us to flourish. Cloud and Townsend, the co-authors of Boundaries , answer that question in Safe People. They start by defining unsafe people, who generally fall into three categories: the abandoners, the critics, and the irresponsibles. We may choose unsafe relationships for a variety of reasons, including: isolation, fear of confrontation, romanticizing, rescuing, and familiarity, among others. Against the backdrop of unsafe people, Cloud and Townsend use Jesus as the ultimate example of a safe person because he embodies dwelling connection , grace, and truth. But what are healthy relationships, and how do we find them? Unsafe people are defensive instead of open to feedback.
Your generosity brings The Global Leadership Summit to more communities worldwide. Learn how you can equip, encourage and inspire Christian influencers globally by providing the access to leadership tools where needed most. We invite you to follow the Summit around the world and learn about the impact of your donations by reading stories and watching videos about leaders who were inspired and empowered to create change in their communities locally and around the globe. Learn and reflect as you listen to faculty like Craig Groeschel in this audio replay of 's inspiring event. Packed with great talks from a variety of faculty like Bear Grylls and Liz Bohannon offering great insights and challenging ideas.
Spiritual and Emotional Roots and Treatment of Addiction - Dr. John Townsend
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If you surf around this website, you would soon discover I am a strong proponent of getting connected in good, safe relationships. It is the underlying ingredient of having a healthy, maturing life. We all want people in our lives that help us in these ways. But how do we recognize them? What do they look like? If we are to begin to utilize safe relationships, we need to first understand what a safe person is and why we need that kind of safety. The best example of a safe person is found in Jesus.