Preface
Focusing on the field of big data analysis, Python has a powerful scientific computing library. Faced with massive data, Python only needs to call several Python libraries: NumPy, pandas (functions and methods for processing data), matplotlib (and scipy (efficient mathematical operations)) to efficiently and accurately solve a large number of data analysis problems, while Java There is no way to compete with Python in these areas.
The rise and development of artificial intelligence in recent years has made Python's advantages more and more obvious. The advantages of Python in terms of automation and machine learning are self-evident.
Getting started with Python is relatively simple. It is recommended to follow the tutorials and practice more.
Below we have prepared super useful information for you - popular python learning videos and excellent python learning videos selected from Station B!
First, let’s sort out the best learning roadmap for Python:
python language basics
- Introduction to Python3, data types, strings
- Judgment/loop statements, functions, namespaces, scopes
- Classes and objects, inheritance, polymorphism
- tkinter interface programming
- Files and Exceptions, Introduction to Data Processing
- Pygame actual aircraft battle, 2048
python language advanced
- Python common third-party libraries and network programming
- Python regular expressions
- Mailbox crawler, file traversal, financial data crawler, multi-threaded crawler
- Python threads and processes
- Python MySQL database, coroutine, jython
python full stack engineer front end
- HTML
- HTML5
- CSS
- CSS3
- Web interface design practice
- javaScript
- jquerry
- Introduction to jquerry EasyUI, Mobile, photoshop
- Bootstrap
python full stack engineer backend
- Getting started with Django
- Django Advanced
- Django actual combat
python full stack engineer backend advanced
- Flask development principles
- Flask development project practice
- Tornado development principles
- Tornado development project practice
Linux basics
- File processing commands
- Rights management commands
- help command
- file search command
- Compression and decompression commands
- Command usage tips
- VIM use
- Package management
- User and user group management
- Linux Shell development
Linux operation and maintenance automation development
- Develop Linux operation and maintenance
- Linux operation and maintenance alarm tool development
- Linux operation and maintenance alarm security audit development
- Linux business quality report tool development
- Kali security detection tool detection
- Kali password cracking practice
python data analysis
- numpy data processing
- pandas data analysis
- matplotlib data visualization
- scipy data statistical analysis
- python financial data analysis
python big data
- Hadoop HDFS
- python Hadoop MapReduce
- python Spark core
- python Spark SQL
- python Spark MLlib
python machine learning
- Introduction to machine learning basics
- KNN algorithm
- linear regression
- logistic regression algorithm
- Decision tree algorithm
- Naive Bayes algorithm
- Support Vector Machines
- Clustering k-means algorithm
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1. Introduction to Python
The following content is the basic knowledge necessary for all application directions of Python. If you want to do crawlers, data analysis or artificial intelligence, you must first learn them. Anything high-end is built on a primitive foundation. By laying a good foundation, the road ahead will be more stable.All information is available for free at the end of the article！！！
Include:
Computer Basics
python basics
Python introductory video episode 600:
Watch zero-based learning videos. Watching videos is the fastest and most effective way to learn. It is easy to get started by following the teacher's ideas in the video, from basic to in-depth.
2. Python crawler
As a popular direction, crawlers are a good choice whether you use them part-time or as an auxiliary skill to improve work efficiency.
Through crawler technology, relevant content can be collected, analyzed and selected to get the information we really need.
This information collection, analysis and integration work can be applied to a very wide range of areas. Whether it is life services, travel, financial investment, product market demand of various manufacturing industries, etc., crawler technology can be used to obtain more accurate and effective information. use.
Python crawler video information
3. Data analysis
The "Digital Transformation of China's Economy: Talent and Employment" report released by Tsinghua University School of Economics and Management shows that the data analysis talent gap is expected to reach 2.3 million in 2025.
With such a huge talent gap, data analysis is like a vast blue ocean! Starting salary of 10K is really commonplace.
4. Database and ETL data warehouse
Enterprises need to regularly transfer cold data from the business database and store it in a warehouse dedicated to storing historical data. Each department can provide unified data services based on its own business characteristics. This warehouse is a data warehouse.
The traditional data warehouse integrated processing architecture is ETL. Using the capabilities of the ETL platform, E = extract data from the source database, L = clean the data (data that does not comply with the rules) and transform the table (perform different dimensions and granularity on the table according to business needs) degree, different business rules calculation and statistics), T=load the processed table to the data warehouse in increments, full quantities, and different times.
5. Machine Learning
Machine learning is to learn from a part of the computer data, and then predict and judge other data.
The core of machine learning is "using algorithms to parse data, learn from it, and then make decisions or predictions about new data." That is to say, the computer uses the data obtained to derive a certain model, and then uses this model to make predictions. This process is somewhat similar to the human learning process. For example, after a person acquires certain experience, he or she can predict new problems.
Machine learning materials:
6. Advanced Python
From basic syntax content to many in-depth advanced knowledge points and understanding of programming language design, after studying here, you will basically understand all the knowledge points from entry to advanced python.
At this point, you can basically meet the company's employment requirements. If you still don't know where to find interview materials and resume templates, I have compiled one here for you. It can really be said to be a systematic learning route for nannies and caregivers. .
But learning programming does not happen overnight, but requires long-term persistence and training. In organizing this learning route, I hope to make progress together with everyone, and I can also review some technical points myself. Whether you are a newbie in programming or an experienced programmer who needs to advance, I believe everyone can gain something from it.
It doesn’t happen overnight, but requires long-term persistence and training. In organizing this learning route, I hope to make progress together with everyone, and I can also review some technical points myself. Whether you are a newbie in programming or an experienced programmer who needs to advance, I believe everyone can gain something from it.
Data collection
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