Slight rewording for clarity.
This commit is contained in:
Roger Labbe
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@ -363,16 +363,14 @@
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"\n",
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"As I began to understand the math and theory more difficulties appeared. A book or paper will make some statement of fact and presents a graph as proof. Unfortunately, why the statement is true is not clear to me, or I cannot reproduce the plot. Or maybe I wonder \"is this true if R=0?\" Or the author provides pseudocode at such a high level that the implementation is not obvious. Some books offer Matlab code, but I do not have a license to that expensive package. Finally, many books end each chapter with many useful exercises. Exercises which you need to understand if you want to implement Kalman filters for yourself, but exercises with no answers. If you are using the book in a classroom, perhaps this is okay, but it is terrible for the independent reader. I loathe that an author withholds information from me, presumably to avoid 'cheating' by the student in the classroom.\n",
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"\n",
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"All of this impedes learning. If you are designing a Kalman filter for a aircraft or missile you must thoroughly master of all of the mathematics and topics in a typical Kalman filter textbook. I just want to track an image on a screen, or write some code for my Arduino project. I want to know how the plots in the book are made, and to choose different parameters than the author chose. I want to run simulations. I want to inject more noise into the signal and see how a filter performs. There are thousands of opportunities for using Kalman filters in everyday code, and yet this fairly straightforward topic is the provenance of rocket scientists and academics.\n",
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"All of this impedes learning.I want to track an image on a screen, or write some code for my Arduino project. I want to know how the plots in the book are made, and to choose different parameters than the author chose. I want to run simulations. I want to inject more noise into the signal and see how a filter performs. There are thousands of opportunities for using Kalman filters in everyday code, and yet this fairly straightforward topic is the provenance of rocket scientists and academics.\n",
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"\n",
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"I wrote this book to address all of those needs. This is not the book for you if you design military radars. Go get a Masters or PhD at a great STEM school, because you'll need it. This book is for the hobbyist, the curious, and the working engineer that needs to filter or smooth data. \n",
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"I wrote this book to address all of those needs. This is not the sole book for you if you design military radars. Go get a Masters or PhD at a great STEM school, because you'll need it. This book is for the hobbyist, the curious, and the working engineer that needs to filter or smooth data. If you are a hobbyist this book should provide everything you need. If you are serious about Kalman filters you'll need more. My intention is to introduce enough of the concepts and mathematics to make the textbooks and papers approachable.\n",
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"\n",
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"This book is interactive. While you can read it online as static content, I urge you to use it as intended. It is written using Jupyter Notebook (formally known as IPython Notebook). This allows me to combine text, math, Python, and Python output in one place. Every plot, every piece of data in this book is generated from Python inside the notebook. Want to double the value of a parameter? Just change the parameter's value, and press CTRL-ENTER. A new plot or printed output will appear. \n",
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"This book is interactive. While you can read it online as static content, I urge you to use it as intended. It is written using Jupyter Notebook. This allows me to combine text, math, Python, and Python output in one place. Every plot, every piece of data in this book is generated from Python inside the notebook. Want to double the value of a parameter? Just change the parameter's value, and press CTRL-ENTER. A new plot or printed output will appear. \n",
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"\n",
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"This book has exercises, but it also has the answers. I trust you. If you just need an answer, go ahead and read the answer. If you want to internalize this knowledge, try to implement the exercise before you read the answer. Since the book is interactive, you enter and run your solution inside the book - you don't have to move to a different environment, or deal with importing a bunch of stuff before starting.\n",
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"\n",
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"If you are a hobbyist this book should provide everything you need. If you are serious about Kalman filters you'll need more. My intention is to introduce enough of the concepts and mathematics to make the textbooks and papers approachable.\n",
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"\n",
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"This book is free. I've spent several thousand dollars on Kalman filtering books. I cannot believe they are within the reach of someone in a depressed economy or a financially struggling student. I have gained so much from free software like Python, and free books like those from Allen B. Downey [1]. It's time to repay that. So, the book is free, it is hosted on free servers at GitHub, and it uses only free and open software such as IPython and MathJax."
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]
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},
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@ -398,9 +396,7 @@
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"\n",
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"<b>binder</b>\n",
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"\n",
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"I am experimentally trying a new service, binder. binder serves interactive notebooks online, so you can run the code and change the code within your browser without downloading the book or installing Jupyter. I have not experimented with it much. Please raise an issue on my GitHub page if anything fails. I'm not officially supporting this as binder is in beta, but I'm quite excited about the possibilities.\n",
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"\n",
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"Use this link to access the book via binder:\n",
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"binder serves interactive notebooks online, so you can run the code and change the code within your browser without downloading the book or installing Jupyter. Use this link to access the book via binder:\n",
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"\n",
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" http://mybinder.org/repo/rlabbe/Kalman-and-Bayesian-Filters-in-Python\n",
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"\n",
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@ -452,7 +448,7 @@
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" \n",
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"This will create a directory named `Kalman-and-Bayesian-Filters-in-Python`. The `depth` parameter just gets you the latest version. Unless you need to see my entire commit history this is a lot faster and saves space. Navigate to the directory, and run Jupyter Notebook with the command\n",
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"\n",
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" ipython notebook\n",
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" jupyter notebook\n",
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"\n",
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"This will open a browser window showing the contents of the base directory. The book is organized into chapters. Each chapter is named *xx*-*name*.ipynb, where *xx* is the chapter number. .ipynb is the Notebook file extension.\n",
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"\n",
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@ -583,8 +579,9 @@
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}
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],
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"metadata": {
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"anaconda-cloud": {},
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"kernelspec": {
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"display_name": "Python 3",
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"display_name": "Python [default]",
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"language": "python",
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"name": "python3"
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},
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@ -598,7 +595,7 @@
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.5.1"
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"version": "3.5.2"
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}
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},
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"nbformat": 4,
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