Python

Book/ TOP 10 FREE PYTHON PDF EBOOKS TO LEARN PYTHON | Leet Tips. Python is a high level programming language which increasingly popular. I have collected 10 free ebooks for python which contains lots of exercises, practices, example programs and many more. Here I have collected 10 Python ebooks for you which may help you to lean python accordingly. 1. A Byte of Python A Byte of Python is a beginner’s book on Python by Swaroop C H. “If all you know about computers is how to save text files, then this is the book for you,” the site says. This book is perfect for any kind of python lover and beginner who wants an easy and progressing way of learning python.

This one also comes under my personal recommendation. 2. 3. 4. 5. 6. 7. 8. 9. Getting Started With Python For Data Science. Who is this for and what will I learn? This tutorial assumes some knowledge of Python and programming, but no knowledge whatsoever of data science, machine learning, or predictive modeling (or, heck, even statistics). To the extent there is a target audience, it's probably hacker types who learn best by doing. All the code from this tutorial is available on github . You might encounter terms you're not familiar with, but that shouldn't stop you from completing the tutorial. By the end, you won't know a heck of a lot more about data science per se , but you'll have a nice environment set up where you can easily play with lots of different data science tools and even make credible entries to Kaggle competitions.

Here's what you'll learn: How to install popular scientific and statistical computing libraries for Python Use those libraries to create a benchmark predictive model and submit it to a competition. Excited? 1. Numpy - (pronounced num-pie ) Powerful numerical arrays. 2. Language: bash. IPython a short introduction. Programming in Python. Online Python Tutor - Learn programming by visualizing code execution. Dive Into Python. Machine learning in Python — scikit-learn 0.13.1 documentation.

Namtaf.mursing.net/python reference.txt. Python Resources | edX Wiki. Skip to this view's content Please enter your e-mail address below, and we will e-mail instructions for setting a new password. Help Have general questions about edX? You can find lots of helpful information in the edX FAQ. Have a question about something specific? Report a problem Make a suggestion Ask a question Please note: The edX support team is English speaking. Thank you for your inquiry or feedback. We're Sorry, edX accounts are unavailable currently The following errors occurred while logging you in: Your email or password is incorrect Please provide the following information to log into your edX account. Required Information Account Preferences. Non-Programmer's Tutorial for Python 3/Print version.

All example Python source code in this tutorial is granted to the public domain. Therefore you may modify it and relicense it under any license you please. Since you are expected to learn programming, the Creative Commons Attribution-ShareAlike license would require you to keep all programs that are derived from the source code in this tutorial under that license. Since the Python source code is granted to the public domain, that requirement is waived. This tutorial is more or less a conversion of Non-Programmer's Tutorial for Python 2.6. Older versions and some versions in Korean, Spanish, Italian and Greek are available from The Non-Programmers' Tutorial For Python 3 is a tutorial designed to be an introduction to the Python programming language. If you have programmed in other languages I recommend using Python Tutorial for Programmers written by Guido van Rossum.

Thanks go to James A. Other resources First things first Hello, World! Halt! Mac users. Think Python: How to Think Like a Computer Scientist. How to Think Like a Computer Scientist by Allen B. Downey This is the first edition of Think Python, which uses Python 2. If you are using Python 3, you might want to use the second edition, which is here. Buy this book at Amazon.com Download Think Python in PDF. Read Think Python in HTML. Example programs and solutions to some problems are here (links to specific examples are in the book). Description Think Python is an introduction to Python programming for beginners. Some examples and exercises are based on Swampy, a Python package written by the author to demonstrate aspects of software design, and to give readers a chance to experiment with simple graphics and animation. Think Python is a Free Book.

If you have comments, corrections or suggestions, please send me email at feedback{at}thinkpython{dot}com. Other Free Books by Allen Downey are available from Green Tea Press. Download Precompiled copies of the book are available in PDF. Earlier Versions Translations and adaptations. The Python Tutorial — Python v3.0.1 documentation. Python is an easy to learn, powerful programming language. It has efficient high-level data structures and a simple but effective approach to object-oriented programming. Python’s elegant syntax and dynamic typing, together with its interpreted nature, make it an ideal language for scripting and rapid application development in many areas on most platforms.

The Python interpreter and the extensive standard library are freely available in source or binary form for all major platforms from the Python Web site, and may be freely distributed. The same site also contains distributions of and pointers to many free third party Python modules, programs and tools, and additional documentation. The Python interpreter is easily extended with new functions and data types implemented in C or C++ (or other languages callable from C). Python is also suitable as an extension language for customizable applications. The Glossary is also worth going through. Good logging practice in Python | Victor Lin's coding notes.

10 Python one liners to impress your friends - /code/blog. Getting started with Python: Tips, Tools and Resources - Lesson in Programming. 1. MIT 6.00x: Introduction to Computer Science and Programming 6.00x is an introduction to using computation to solve real problems. The course is aimed at students with little or no prior programming experience who have a desire to understand computational approaches to problem solving. This is an amazing course!

This will give you a better overview and depth than any other resource available. I would totally recommend signing up for this course. The examples and exercises give are really good and you will certainly get a good grip over Python after completing this. 2. This course is designed to help students with very little or no computing background learn the basics of building simple interactive applications. 3. This course introduces the fundamental building blocks of programming and teaches you how to write fun and useful programs using the Python language. Second Try: Sentiment Analysis in Python : Andy Bromberg. Introduction After my first experiments with using R for sentiment analysis, I started talking with a friend here at school about my work. Jackson and I decided that we’d like to give it a better shot and really try to get some meaningful results. After a lot of research, we decided to shift languages to Python (even though we both know R).

We made this shift because Python has a number of very useful libraries for text processing and sentiment analysis, plus it’s easy to code in. We launched right into tutorials and coding, and this post will be about that process and our results. We also met with Christopher Potts, a professor of linguistics here at Stanford. If you’d like to jump straight to seeing the full code, you can head over to the GitHub repository. The Setup One of the resources we got a lot of mileage out of was StreamHacker, especially the articles on basic techniques, precision and recall. and eliminating features. Now, thanks to NLTK, I can very simply train my classifier: Welcome to Problem Solving with Algorithms and Data Structures — Problem Solving with Algorithms and Data Structures.

CPython Compilers. Machine Learning in Python Has Never Been Easier! « The Official Blog of BigML.com. At BigML we believe that over the next few years automated, data-driven decisions and data-driven applications are going to change the world. In fact, we think it will be the biggest shift in business efficiency since the dawn of the office calculator, when individuals had “Computer” listed as the title on their business card. We want to help people rapidly and easily create predictive models using their datasets, no matter what size they are. Our easy-to-use, public API is a great step in that direction but a few bindings for popular languages is obviously a big bonus.

Thus, we are very happy to announce an open source Python binding to BigML.io, the BigML REST API. You can find it and fork it at Github. The BigML Python module makes it extremely easy to programmatically manage BigML sources, datasets, models and predictions. The snippet below sketches how you can create a source, dataset, model and then a prediction for a new object. Just like magic! Like this: Like Loading... (143) Python (programming language): What are some good resources to learn data analysis with python? Python Course: Introduction into NumPy.

Introduction NumPy is an acronym for "Numeric Python" or "Numerical Python". It is an open source extension module for Python, which provides fast precompiled functions for mathematical and numerical routines. Furthermore, NumPy enriches the programming language Python with powerful data structures for efficient computation of multi-dimensional arrays and matrices. The implementation is even aiming at huge matrices and arrays. Besides that the module supplies a large library of high-level mathematical functions to operate on these matrices and arrays. SciPy (Scientific Python) is often mentioned in the same breath with NumPy. SciPy extends the capabilities of NumPy with further useful functions for minimization, regression, Fourier-transformation and many others. Both NumPy and SciPy are usually not installed by default. (Comment: The diagram of the image on the right side is the graphical visualisation of a matrix with 14 rows and 20 columns. A Simple Numpy Example.

Python Quick Hacks and Codes. Dive Into Python. Video: Programming GPUs with Python. Using the web browser in Python. A Gentle Introduction to Programming Using Python | Electrical Engineering and Computer Science. Python Shortcuts for the Python Beginner - Max Burstein's Blog. Python Shortcuts for the Python Beginner (Posted on January 26th, 2013) The following are just a collection of some useful shortcuts and tools I've found in Python over the years.

Hopefully you find them helpful. Swapping Variables x = 6y = 5x, y = y, xprint x>>> 5print y>>> 6 Inline if Statement print "Hello" if True else "World">>> Hello Concatenations The last one is a pretty cool way to combine objects of two different types. nfc = ["Packers", "49ers"]afc = ["Ravens", "Patriots"]print nfc + afc>>> ['Packers', '49ers', 'Ravens', 'Patriots']print str(1) + " world">>> 1 worldprint `1` + " world">>> 1 worldprint 1, "world">>> 1 worldprint nfc, 1>>> ['Packers', '49ers'] 1 Number Tricks #Floor Division (rounds down)print 5.0//2>>> 2#2 raised to the 5th powerprint 2**5>> 32 Be careful with division and floating point numbers. print .3/.1>>> 2.9999999999999996print .3//.1>>> 2.0 Numerical Comparison This is a pretty cool shortcut that I haven't seen in too many languages.

List Comprehension Into this: S Python Class - Educational Materials. Welcome to Google's Python Class -- this is a free class for people with a little bit of programming experience who want to learn Python. The class includes written materials, lecture videos, and lots of code exercises to practice Python coding. These materials are used within Google to introduce Python to people who have just a little programming experience. The first exercises work on basic Python concepts like strings and lists, building up to the later exercises which are full programs dealing with text files, processes, and http connections.

The class is geared for people who have a little bit of programming experience in some language, enough to know what a "variable" or "if statement" is. Beyond that, you do not need to be an expert programmer to use this material. This material was created by Nick Parlante working in the engEDU group at Google. Special thanks for the help from my Google colleagues John Cox, Steve Glassman, Piotr Kaminski, and Antoine Picard. Learn to code. Code Like a Pythonista: Idiomatic Python.

In this interactive tutorial, we'll cover many essential Python idioms and techniques in depth, adding immediately useful tools to your belt. There are 3 versions of this presentation: ©2006-2008, licensed under a Creative Commons Attribution/Share-Alike (BY-SA) license. My credentials: I am a resident of Montreal,father of two great kids, husband of one special woman,a full-time Python programmer,author of the Docutils project and reStructuredText,an editor of the Python Enhancement Proposals (or PEPs),an organizer of PyCon 2007, and chair of PyCon 2008,a member of the Python Software Foundation,a Director of the Foundation for the past year, and its Secretary. In the tutorial I presented at PyCon 2006 (called Text & Data Processing), I was surprised at the reaction to some techniques I used that I had thought were common knowledge.

Many of you will have seen some of these techniques and idioms before. These are the guiding principles of Python, but are open to interpretation. Import this. Building Skills in Python — Building Skills in Python. A Programmer’s Introduction to Python Legal Notice This work is licensed under a Creative Commons License. You are free to copy, distribute, display, and perform the work under the following conditions: Attribution. For any reuse or distribution, you must make clear to others the license terms of this work.

Language Basics The Processing View A programming language involves two closely interleaved topics. This part describes the most commonly-used Python statements, sticking with basic numeric data types. Some of the examples in this part refer to the rules of various common casino games. We’ll provide a little background on Python in Background and History. In Simple Numeric Expressions and Output we’ll introduce the print statement (and print() function); we’ll use this to see the results of arithmetic expressions including the numeric data types, operators, conversions, and some built-in functions. Data Structures The Data View Expression Statement. The Other Side of the Coin. Sequences.

Learn Python The Hard Way. Think Complexity. By Allen B. Downey Buy this book from Amazon.com. Download this book in PDF. Read this book online. Description This book is about complexity science, data structures and algorithms, intermediate programming in Python, and the philosophy of science: Data structures and algorithms: A data structure is a collection that contains data elements organized in a way that supports particular operations. This book focuses on discrete models, which include graphs, cellular automata, and agent-based models. Complexity science is an interdisciplinary field---at the intersection of mathematics, computer science and physics---that focuses on these kinds of models. Free books! This book is under the Creative Commons Attribution-NonCommercial 3.0 Unported License, which means that you are free to copy, distribute, and modify it, as long as you attribute the work and don't use it for commercial purposes.

Download the LaTeX source code (with figures and a Makefile) in a zip file. Think Python: How to Think Like a Computer Scientist. Non-Programmer's Tutorial for Python 2.6. Text Processing in Python (a book) The Python Tutorial. Download Course Materials | A Gentle Introduction to Programming Using Python | Electrical Engineering and Computer Science. Python. Codecademy. ← Python For Beginners. Www.greenteapress.com/thinkpython/thinkpython.pdf. Python Course: Tutorial, Reference and Advanced Topics. Python programming language. Python Learning Resources.