I've seen a lot Python Tutorials and books , Most of them say that Python:
First from Python Development history of , Introduce Python The basic grammatical rules of ,Python Of list, dict, tuple And so on , Then I'll talk about string processing and regular expressions , Introduction documents, etc IO operation , Introduce exception handling again , It's just one chapter at a time .
Many of them are boring theories , The more you look, the more tired you are , The more tired I am, the less I want to see it .
that , Is there a better way ?
Because I've had that “ self-taught ” Python The confused period of , So I know a good systematic study plan and teacher's explanation , It's the key to save more youth of our programmers .
So I extracted more than five years of work experience , And studying in American universities AI The professional postdoctoral teacher wrote this together 60 God's column .
When other teachers introduce knowledge points, they will say “ What is this thing ”, But I don't want to . I think “ Why is this thing like this ” perhaps “ What's the advantage of adapting to what's needed in what scene ”, On the contrary, it will make you have a deeper understanding of knowledge itself .
In line with Interesting and interesting , Dry and pure , Practical first Principles , Five features of the column :
First of all , Case teaching . It's boring to learn pure theoretical knowledge , But combined with a small case , In this way , It's better to learn .
second , Try to be fun . illustrated , Add interesting examples 、 Interesting little projects , More fun to learn .
Third , Self system . Like a detective film , Step-by-step , To spread out one by one Python Technology stack .
Fourth , Dissect some Python Common interview questions . Explain theoretical knowledge , Combined with cases , At the same time, relevant interview questions , Get through the theoretical knowledge thoroughly .
The fifth , Project practice . Not only will there be a real combat environment deployment plan , And the actual project :Python GUI Development projects ,Kaggle Data analysis project , Machine learning project .
In order to let you in self-study can be based on their own learning basis tailor , I will be the whole Python Content By day , Not only can you lighten your daily study burden , And it can test the learning effect more effectively .
Day 1:Python Two characteristics and four basic grammars
Day 2:Python Summary of four data types
Day 3:list and tuple Basic operation 、 Detailed operation of deep and shallow copy and slice, etc 5 Summary of aspects ( With graphic image explanation )
Day 4:list and tuplel Of 13 Classic use cases
Day 5:dict and set Basic operation 、 Dictionary view, etc 6 Detailed explanation and summary of various aspects with graphic explanation
Day 6:dict and set Of 15 Classic use cases
Day 7: Mathematical operations 、 Logical operation and base conversion related 16 Built in functions
Day 8:16 Type functions and 10 Built in function large scale points related to class objects
Day 9:Python String and regular introduction summary
Day 10:Python File operations 11 Summary of cases
Day 11:Python Time module uses logical big board point
Day 12:Python Summary of four common development environments
Day 13:Python Installation package common problems and solutions , Through two practical cases
Day 14: Five minutes to get started 7 individual Web、 Reptiles 、 Packaging tools Pyinstaller Equal package introduction and introduction case summary
Day 15: Five minutes to get started 8 Data analysis 、 Machine learning and deep learning package and framework and introduction case summary
Day 16:Pyinstaller Packaging process details
Day 17:Python List generation efficient 12 A case
Day 18:Python Equality comparison between objects is,in,id,== And so on
Day 19:yield Keyword and generator usage four aspects summary and three examples ,nonlocal Key words and global Keyword Usage Summary
Day 20: Higher order function 、 iterator 、 Decorator, etc 20 Built in function big board point
Day 21:Python Apply three regular cases and recommend a regular verification tool
Day 22:Python Multithreading use logic easy to understand summary
Day 23:Python Summary of efficient memory saving methods ( Further improve yield usage )
Day 24:Python The most underrated Library collections Use summary
Day 25:Python Five types of arguments to a function ,inspect Module view parameter type and parameter assignment rule summary
Day 26:Python Functional programming summary , Including closures ,nonlocal Summary of the use of keywords
Day 27:Python The essence of decorator , Combined with three cases of decorators
Day 28:Python common 12 A collection of pits
Day 29:NumP Getting started using logic efficiently , Master these five functions
Day 30:NumPy Advanced and efficient use logic , Master these five functions
Day 31:NumPy Interpretation and application of broadcasting mechanism rules of
Day 32:Pandas Five kinds of questions about reading and writing documents and 38 Summary of parameters
Day 33:Pandas Stronger bracket operation ,iterrows, itertuples and merge Comparative analysis of processing speed , Peculiar set_index,reset_index,reindex operation
Day 34:Pandas The pivoting function 4 Summary of the use of large functions
Day 35:Pandas There are two ways to split data , Convert to dummy variable (dummy) Two methods of , A summary of four different ways to connect two tables
Day 36: Develop common exception summary :Unhashable Type, Reading files is the most common 4 Exceptions ,SettingWithCopyWarning
Day 37: The drawing is amazing Pyecharts A quick and detailed summary of the methods on hand , from Charts and Options Start with two modules
Day 38:Matplotlib Drawing principle summary , Three methods of drawing multiple graphs are summarized ,12 A complete code analysis and animation method summary of the commonly used graph
Day 39: be based on Kaggle Movie Review datasets Pandas Data analysis practice - Data preprocessing stage
Day 40: be based on Kaggle Movie Review datasets Pandas Data analysis practice - Dig out comedy Top50 The list
Day 41:PyQt Make GUI actual combat : Learn to use by making small and beautiful calculators PyQt
Day 42: About the entry algorithm 、 Machine learning and deep learning are some of my thoughts
Day 43: Eight sorting algorithm principle summary and Python Complete code implementation
Day 44: Dynamic programming algorithm and case summary
Day 45: Interviews often test Leetcode Algorithm analysis and summary
Day 46: Necessary statistical knowledge : probability , expect , variance , Standard deviation , covariance , The correlation coefficient ,t test ,F test , Chi square test
Day 47: Basic mathematics knowledge for machine learning : The most commonly used derivation formula , Matrix eigenvalue decomposition, etc
Day 48: Concepts that machine learning has to know : sample space , Eigenvector , dimension , Generalization ability , Inductive preference, etc
Day 49: Machine learning 9 A common probability distribution
Day 50:OLS Linear regression practice part 1 : A detailed introduction to the regression principle of machine learning , Including assumptions and principles , Gradient descent for weight
Day 51:OLS Linear regression practice 2 : The implementation of linear regression algorithm without packet transfer by handwriting
Day 52: Analysis and compilation of Bayesian classification cases
Day 53: Practical application of Bayesian algorithm : Implement word spell corrector
Day 54: Analysis and solution summary of clustering principle of Gaussian mixture model
Day 55: Cluster model practice : Multi dimension data clustering case without packet transfer
Day 56: Machine learning commonly used clustering algorithm includes the principle and use considerations
Day 57: Machine learning dimension reduction algorithm PCA Principle derivation and example analysis
Day 58:Kaggle Machine learning classification task case practice
Day 59: Doctor of famous universities in the United States 、AI Experts Alicia How to learn mathematics 、 machine learning 、 Summary of data analysis
Day 60: Column summary and my past 5 Years of algorithm experience sharing
author 1:zglg,5 Years working experience in algorithm development , Senior algorithm engineer of famous Internet company , Created Python Case study GitHub One month in the library star Quantity from 0 To 1700+, By AI Quantum report of authoritative media .
author 2:Alicia, Ph.D. in mathematics from a famous American school , HP Senior Data Analyst , Currently studying in the top universities in the United States AI Professional postdoctoral , Rich experience in work and scientific research .
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