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Wednesday, December 28, 2022
Inverted index construction - Information Retrieval
Tuesday, December 27, 2022
Evaluation Measures - Information Retrieval
Confusion Matrix : https://towardsdatascience.com/understanding-confusion-matrix-a9ad42dcfd62
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Functional View of Paradigm IR System - Information Retrieval
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The Process of Retrieving Information -- Information Retrieval
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Data Retrieval vs Information Retrieval....
1. Matching.
In data retrieval we are normally looking for an exact match, that is, we are checking to see whether an item is or is not present in the file.
Ex: Select * from Student where per >= 8.0
In information retrieval more generally we want to find those items which partially match the request and then select from those a few of the best matching ones.
Ex: Student having 8 or > 8 CGPA
2. Inference
In data retrieval is of the simple deductive kind, that is, a ∈ b and b ∈ c then a ∈ c.
In information retrieval it is of inductive inference; relations are only specified with a degree of certainty or uncertainty and hence our confidence in the inference is variable.
3.Model
Data retrieval is deterministic but information retrieval is probabilistic.
Frequently Bayes' Theorem is invoked to carry out inferences in IR, but in DR probabilities do not enter into the processing.
4 .Classification:
In DR most likely monothetic classification is used.
That is, one with classes defined by objects possessing attributes both necessary and sufficient to belong to a class.
In IR, polythetic classification is mostly used.
Each individual in a class will possess only a proportion of all the attributes possessed by all the members of that class..
5.Query Language:
The query language for DR is one with restricted syntax and vocabulary.
In IR we prefer to use natural language although there are some notable exceptions.
6.Query Specification:
In DR the query is generally a complete specification of what is wanted,
In IR it is invariably incomplete.
7.Items wanted :
In IR we are searching for relevant documents as opposed to exactly matching items in DR.
8.Error response:
DR is more sensitive to error in the sense that, an error in matching will not retrieve the wanted item which implies a total failure of the system.
In IR small errors in matching generally do not affect performance of the system significantly
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Thursday, September 29, 2022
BITS-WILP-DSECLZG555 - Data Visualization and Interpretation - DVI - Final Question paper - 25092022
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BITS-WILP-DSECLZG565 - Machine Learning - ML - Final Question paper - 25092022
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BITS-WILP-DSECLZG523 - Introduction to Data Science - IDS - Final Question paper - 18092022
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BITS-WILP-DSECLZC413- Introduction to Statistical Methods - ISM - Final Question paper - 18092022
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Saturday, September 24, 2022
DSECLZG565- MACHINE LEARNING - Quick Calculators
SVM (linear and Non liner ) : https://www.javatpoint.com/machine-learning-support-vector-machine-algorithm
algorithm : https://towardsdatascience.com/support-vector-machine-formulation-and-derivation-b146ce89f28
K means Cluster calculator : https://people.revoledu.com/kardi/tutorial/kMean/Online-K-Means-Clustering.html
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DSECLZG555-DATA VISUALIZATION AND INTERPRETATION - Story Telling Strategies
Establishing Context
who : Audience and you
what : Action , Mechanism and Tone
How : Data
Story Telling Strategies
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1. 3 Minute Story - telling the story with in 3 mins just by telling audience hat they need to know . No dependency on materials/visualization etc
Story teller needs to know what exactly data is saying .
2. Big idea -- Boils down to most importance sentence. It should articulate unique point of view / convey whats at stake / must be complete sentence .
3. Story boarding -- Establishes structure of communication. Visual outline of content . Use whiteboard , post -it etc.
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DSECLZG555 - DATA VISUALIZATION AND INTERPRETATION - Gestalt Principles of Visual Perception
- Law of Prägnanz (Simplicity)
- Law of Similarity
- Law of Continuity
- Law of Focal Point
- Law of Proximity
- Law of Figure/Ground
- principle of enclosure
- principle of closure
- principle of continuity
- principle of connection
- principle of proximity
- principle of similarity
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DSECLZG555 - DATA VISUALIZATION AND INTERPRETATION - Mistakes in Dashboard design
Mistakes in dashboard
1. Design issues
a. Exceeding screen
b. meaningless variety
c. Clustering display
d. Unattractive visuals
2. Data Issues
a. Inadequate context for the data
b. Using deficient measure
c. Incorrect data encoding
d. Poor data arrangement
e. Ineffective data highlighting
3. Display Issues
a. Inappropriate display media
poorly designed display media
13 Design Mistakes
1.Exceeding the Boundaries of a Single Screen
2. Supplying Inadequate Context for the Data
3. Displaying Excessive Detail or Precision
4. Choosing a Deficient Measure
5. Choosing Inappropriate Display Media
6. Introducing Meaningless Variety
7. Using Poorly Designed Display Media
8. Encoding Quantitative Data Inaccurately
9. Arranging the Data Poorly
10. Highlighting Important Data Ineffectively
11. Cluttering the Display with Useless Decoration
12. Misusing or Overusing Color
13. Designing an Unattractive Visual Display
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Easy way of converting google colab ipynb to a PDF file
Below steps are to be performed to convert ipynb file to PDF file.
1. Install below packages for every ipnyb file
!apt-get install texlive texlive-xetex texlive-latex-extra pandoc
!pip install pypandoc
2. Copy the path of the file [Ex: File name : abc.ipynb]
3. Execute below
!jupyter nbconvert <<path+ filename>> --to pdf
Ex : !jupyter nbconvert /content/drive/MyDrive/Colab/ForExam-Seaborn.ipynb --to pdf
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Saturday, September 17, 2022
BITS WILP - DSECLZC413 - Introduction to Statistical Methods - Important calculators
Calculators
Chi Square Test Contingency Table : https://www.socscistatistics.com/tests/chisquare2/default2.aspx
Chi-Square Calculator for Goodness of Fit : https://www.socscistatistics.com/tests/goodnessoffit/default2.aspx
Easy Fisher Exact Test Calculator : https://www.socscistatistics.com/tests/fisher/default2.aspx
T-Test Calculator for 2 Independent Means : https://www.socscistatistics.com/tests/studentttest/default.aspx
T Test Calculator for 2 Dependent Means : https://www.socscistatistics.com/tests/ttestdependent/default.aspx
Single Sample T-Test Calculator : https://www.socscistatistics.com/tests/tsinglesample/default.aspx
Pearson Correlation Coefficient Calculator : https://www.socscistatistics.com/tests/pearson/default.aspx
Spearman's Rho Calculator :https://www.socscistatistics.com/tests/spearman/default.aspx
Linear Regression Calculator : https://www.socscistatistics.com/tests/regression/default.aspx
Multiple Regression Calculator (No residual calculation) : https://www.socscistatistics.com/tests/multipleregression/default.aspx
Maximium Likelyhood estimator : https://mathworld.wolfram.com/MaximumLikelihood.html
Z-test: One Population Proportion : https://mathcracker.com/z-test-for-one-proportion
4 year moving average calculator : https://atozmath.com/CONM/TimeSeries.aspx?q=smaf
autocorrelation : https://www.easycalculation.com/statistics/autocorrelation.php
autocovariance formula :
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