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Python for beginners using sample projects.

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.

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