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If you want to use Django + Bootstrap to write a website, which books or videos are relatively systematic and complete?

including: 1. Movie display, which is the focus, filtering, and searching; 2. The question of film is the question of seeking seeds; 3. online chat, which is not perfect, can only be online chat; 4. Management of basic user information, logon and registration, etc; Demo address: http: // 121.42.156.185: 8000/getmovielist/ (The domain name has not been filed .. That's it. About 16000 movies can be played) Github address: https://github.com/pureYun/dnomovie You don't need to read any books to add

2017 front-end Performance tuning checklist

layout and decoration of work for canvas-free browsing, or on third-party tools. To ensure that there is no delay in scrolling and animating the page, don't forget the 60 frames per second principle mentioned earlier. If there is no way to do this, make sure that the frame number per second is roughly within 15 to 60 frames. Use Will-change in CSS to inform the browser which elements and attributes have changed.Also remember to measure performance in rendering execution (you can use Devtools).

The 100-hour Rule

hours of active learning to become much more competent than a absolute be Ginner. For example: cooking:it takes years to become a master chef , but one hundred hours of cooking lessons and classes and deliberate practice would make you a better cook than most of yo ur friends. coding:it takes years of study and practice to Become a strong software engineer, but going through a couple of codecademy or Udacity courses would make you

Performance Optimization 2 Rendering

Android Performance Optimization Rendering ChapterAPR 11TH, 2015 | COMMENTS Google recently launched an Android performance-optimized online course on Udacity, which describes how to optimize performance from rendering, computing, and memory, to power These are the refinements and additions to the Android performance optimization paradigm that Google has previously published on YouTube. The following is the rendering of the text of the s

A very useful programming story

learn Python through reading and Udacity courses.After seven months of hard work, I got my first job as a software engineer.When the CTO interviewed me, I told him all the tools I had learned and the tall profiles I was using. The CTO listened to me politely and nodded from time to time. After I bragged about my profound knowledge, he looked at me and said, "in fact, most things have a lot of solutions, but only a very small part of it is meaningful"

A very useful programming story

this). Objectively speaking, this is one of the most efficient keyboard layouts for programmers.Looking at the above keyboard layout, can you tell me how many letter keys, number keys, special character key position has not changed? The answer is single digit.When I was able to start Linux successfully and I could knock out 10 words in a minute, I began to learn Python through reading and Udacity courses.After seven months of hard work, I got my firs

A useful programming story and Value-Oriented Programming story

tell me how many keys, numbers, and special character keys have not changed? The answer is the single digit.When I was able to start Linux successfully, I began to learn Python through reading books and Udacity courses when I was able to break ten words in a minute.After seven months of hard work, I got my first job as a software engineer.When the CTO interviewed me, I told him all the tools I had learned and the configuration files I was using. CTO

Python implementation of A * algorithm

. Keys: current := camefrom[current total_path. Append (current) return total_ Path The following is a path planning project in the Udacity course, combined with the pseudocode above, to implement a * with PythonImport mathdef Shortest_path (m,start,goal): SX=m.intersections[start][0] Sy=m.intersections[start][1] GX=m.intersections[goal][0] Gy=m.intersections[goal][1] H=math.sqrt ((SX-GX) * (SX-GX) + (sy-gy) * (sy-Gy)) Closedset=Set()

[resource-] Python Web crawler & Text Processing & Scientific Computing & Machine learning & Data Mining weapon spectrum

python machine learning Toolkit Scikit-learn and related video –tutorial:scikit-learn–machine are recommended learning In PythonOfficial homepage: http://scikit-learn.org/2. Pandas:python Data Analysis Library Pandas is a software library written for the Python programming language for data manipulation and analysis. In particular, it offers the data structures and operations for manipulating numerical tables and time series. The first contact with pandas was due to the

For beginners to Python: Anaconda Getting Started using the guide

Exit the current environment: 1 Source Deactivate Also note that in Windows systems, use activate env_name and deactivate to enter and exit an environment.To remove an environment named Env_name: 1 Conda Env Remove - n env_name Show All environments: 1 Conda Env List When sharing the code, but also need to share the environment to everyone, execute the following command can

Draw flag with Python's turtle module

EditDraw flag with Python's turtle module In Udacity class, learned the Python turtle method, this is a very classic to teach children programming graphics module, originally originated from the logo language. Python itself has built-in this module, and its visual approach can help children understand some of the basic concepts of programming.In the job submission forum to see a lot of turtle drawing out of the beautiful graphics, can not thi

Run Python (MAC)-Overview __python

code. If you are using a different editor and want to implement this feature, you can search Google for instructions on how to do this, or visit the Udacity forum for help. Method 2: Use the command line It may be convenient to run and display Python's output using a text editor, but most developers also know how to run code using the command line. This process still starts with writing and saving code from a text editor, but instead of requiring the

Machine learning notes (b) univariate linear regression

Machine learning notes (b) univariate linear regression Note: This content resource is from Andrew Ng's machine learning course on Coursera, which pays tribute to Andrew Ng. Model representationHow to solve the problem of house price in note (a), this will be the focus of this article. Now, assuming that there is more housing price data, a straight line is needed to approximate the trend of house prices, as shown in: Review the concept

[Book]awesome-machine-learning Books

prediction Naturual Language Processing Coursera Course Book on NLP NLTK NLP W/python Foundations of statistical Language processing Probability Statistics Thinking Stats-book + Python Code From algorithms to Z-scores-book The Art of R Programming-book (not finished) All of Statistics Introduction to statistical thought Basic probability theory Introduction to probability Principle of u

Robot Learning Cornerstone (Machine learning foundations) Learn Cornerstone Job four q13-20 MATLAB implementation

Hello everyone, I am mac Jiang, today and everyone to share the coursera-ntu-machine learning Cornerstone (Machines learning foundations)-Job four q13-20 MATLAB implementation. The previous code was implemented through C + +, but found that C + + implementation of the code is too cumbersome, the job also to change the parameter values frequently, so choose to use MATLAB to achieve. Compared with C + +, Matlab is obviously much easier to implement and

25 Excellent website recommendations that make you more intelligent and powerful

. Coursera More than 120 of the top university courses are available for free study and viewing. Gibbon You can use Gibbon to collect and share knowledge, whether it's for your team or for the world, it's not a problem. 99U YouTube Channel 99U is Behance's research and education organization, and on their YouTube channel, you'll find a lot of knowledge about efficiency, organization, leadership, design, and thinking. Infographics Here you will

Stanford Algorithms (a): Multiply by large number (C + +)

Stanford Algorithms (a): Multiply by large number (C + +)Just not in the Chinese university Mooc attended the course of Chen teacher 数据结构 , Harvest very big. Feel the strike, also put the algorithm part also to a school, on the Coursera registered a Stanford University algorithm class, the amount of the course is very heavy, estimated to learn a semester, slowly learn, steady.The course recommended a lot of books, I found a book, the title is called A

Robot Learning Cornerstone (Machine learning foundations) Learn Cornerstone Job four q13-20 MATLAB implementation

Hello everyone, I am mac Jiang, today and everyone to share the coursera-ntu-machine learning Cornerstone (Machines learning foundations)-Job four q13-20 MATLAB implementation.Once the code is implemented through C + +. However, it is too cumbersome to discover that C + + implements this code. This job also need to change the number of participants frequently, so choose to use MATLAB to achieve. Compared to C + +. MATLAB implementation is obviously mu

Python module learning question No. 0000

fromPILImportImage, Imagedraw, Imagefont7 8sourceFileName ="classic.jpg"9Avatar = Image.open (sourceFileName)#Open picture FileTenDrawavatar = Imagedraw.draw (Avatar)#Create a brush to write numbers on a picture One AMyFont = Imagefont.truetype ("C:/windows/fonts/simsunb.ttf", 60)#write with a specific font - -Drawavatar.text ([in], text="9", fill= (255, 0, 0), font=MyFont) the - avatar.show () -Avatar.save ('classic_pil.jpg')This time, learn to save the picture, say OpenCV Save the picture

Algorithm interview course Note 001 Algorithm interview what the hell is that?

excellentAlgorithmic interviewing is only part of the technical interview.Depending on your CV and the position you are applying for, there are other technical aspects to be explored.Technical Interview Content: (depending on your position) Project experience and practical problems encountered in the project What is the most impressive bug you have ever encountered? Object oriented Design Patterns Network-related, security-related, memory-related, concurrency-related;

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