Python for beginners using sample projects.
Bei: $19.99
What’s the best way to learn any technology , by doing a PROJECT. That’s what exactly this tutorial intends to do. This course teaches Python machine learning using project based approach. Below is the full syllabus for the same. Furaha ya Kujifunza.
Sura 1:- Installing Python framework and Pycharm IDE.
Sura 2:- Creating and Running your first Python project.
Sura 3:- Python is case-sensitive
Sura 4:- Vigezo, Mfumo wa Umwagiliaji wa Smart, inferrence & wanachukuliwa kuwa sehemu ya kundi hili la chakula()
Sura 5:- Python is a dynamic language
Sura 6:- Comments in python
Sura 7:- Creating function, whitespaces & indentation
Sura 8:- Importance of new line
Sura 9:- List in python, Kielezo, Range & Negative Indexing
Sura 10:- For loops and IF conditions
Sura 11:- PEP, PEP 8, Python enhancement proposal
Sura 12:- ELSE and ELSE IF
Sura 13:- Array vs Python
Sura 14:- Reading text files in Python
Sura 15:- Casting and Loss of Data
Sura 16:- Referencing external libararies
Sura 17:- Applying linear regression using sklearn
Sura 18:- Creatiing classes and objects.
Sura 19:- What is Machine learning?
Sura 20:- Algoritham and Training data.
Sura 21:- lakini haifanyi yaliyomo katika hisabati kuwa tofauti.
Sura 22:- Models in Machine Learning.
Sura 23:- Features and Labels.
Sura 24:- Bag of words.
Sura 25:- Implementing BOW using SKLearn.
Sura 26:- The fit Method.
Sura 27:- StopWords.
Sura 28:- The transform Method.
Sura 29:- Zip and Unzip.
Sura 30:- Project Article Auto tagging.
Sura 31 :- Understanding Article auto tagging in more detail.
Sura 32 :- Planning the code of the project.
Sura 33 :- Looping through the files of the directory.
Sura 34 :- Reading the file in the document collection
Sura 35 :- Understanding Vectorizer , Document and count working.
Sura 36 :- Calling Fit and Transform to extract Vocab and Count.
Sura 37 :- Understanding the count and Vocab collection data.
Sura 38 :- Count and Vocab structure complexity
Sura 39 :- Converting CSR matrix to COO matrix
Sura 40 :- Creating the BOW text file.
Sura 41 :- Restricting Stop words.
Sura 42 :- Array vs List revisited
Sura 43 :- Referencing Numpy and Pandas
Sura 44 :- Creating a numpy array
Sura 45 :- Numpy Array vs Normal Python array
Sura 46 :- Why do we need Pandas ?
Sura 47 :- Revising Arrays vs Numpy Array vs Pandas
Sura 47 :- Corupus / Documents, Document and Terms.
Sura 48 :- Understanding TF
Sura 49 :- Understanding IDF
Sura 50 :- TF IDF.
Sura 51 :- Performing calculations of TF IDF.
Sura 52 :- Implementing TF IDF using SkLearn
Sura 53 :- IDF calculation in SkLearn.
Acha jibu
Lazima Ingia au kujiandikisha kuongeza maoni mapya .