Pinned Repositories
Bleualign
Machine-Translation-based sentence alignment tool for parallel text
crime_in_canada
Emergency Data
Data-Augmentation-in-NLP
Document-Analysis
forest-fires
SAS (Data Mining)
gachalign
Gale-Church sentence aligner with options for variable parameters
Inferencing-using-Distilbert
INTEREST-RATE-VOLATILITY-THE-YIELD-CURVE-AND-BOND-PRICING
Start by looking at the Government of Canada bonds, specifically, their yield to maturity (YTM) metric. First, graph YTM curve. Observe shape of the yield curve; see how it changes through time. Pay attention to 3 different type of curve movements – level (e.g. 10-year note YTM changes), slope (e.g. spread between 10Y and 2Y bonds, curvature (e.g. butterfly made up of 2y, 10y and 30y bonds) Once you get that base intuition, try to apply PCA. See if you can normalize PCA components into level effect, slope and curve. Once it is done, progress to ML framework. Inputs should be YTMs again.
mt
Named-Entity-Recognition
simrankaurjolly16's Repositories
simrankaurjolly16/Bleualign
Machine-Translation-based sentence alignment tool for parallel text
simrankaurjolly16/crime_in_canada
Emergency Data
simrankaurjolly16/Data-Augmentation-in-NLP
simrankaurjolly16/Document-Analysis
simrankaurjolly16/forest-fires
SAS (Data Mining)
simrankaurjolly16/gachalign
Gale-Church sentence aligner with options for variable parameters
simrankaurjolly16/Inferencing-using-Distilbert
simrankaurjolly16/INTEREST-RATE-VOLATILITY-THE-YIELD-CURVE-AND-BOND-PRICING
Start by looking at the Government of Canada bonds, specifically, their yield to maturity (YTM) metric. First, graph YTM curve. Observe shape of the yield curve; see how it changes through time. Pay attention to 3 different type of curve movements – level (e.g. 10-year note YTM changes), slope (e.g. spread between 10Y and 2Y bonds, curvature (e.g. butterfly made up of 2y, 10y and 30y bonds) Once you get that base intuition, try to apply PCA. See if you can normalize PCA components into level effect, slope and curve. Once it is done, progress to ML framework. Inputs should be YTMs again.
simrankaurjolly16/mt
simrankaurjolly16/Named-Entity-Recognition
simrankaurjolly16/NER-OCR
simrankaurjolly16/NTU-MC
Nanyang Technological University - Multilingual Corpus (STB subcorpora)
simrankaurjolly16/Python-EDA-Machine-Learning
simrankaurjolly16/smt
Statistical Machine Translation implementation with Python: especially IBM Model1, 2, and phrase-based machine translation.
simrankaurjolly16/Stock_Analysis
StockAnalysis
simrankaurjolly16/Tableau_Sales_Analysis
simrankaurjolly16/Tableau_Waterborn_diseases
simrankaurjolly16/TimeSeriesAnalysis