
R&D Engineer
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NLP-Embedding-Concepts
June 3, 2025 – June 3, 2025
This is a notebook to understand the different Embedding methods of Natural Language Processing (NLP)
View ProjectAdvance-Packages-of-R
April 22, 2019 – April 22, 2019
There are some which are very useful if you are a fan of R. while writing a code line by line for exploratory Data Analytics these libraries helps us to do so in one line of code.
View ProjectPython-Tutorial
October 27, 2018 – October 29, 2018
Python Practice from Coursera- All the tutorials are created under spyder environment. From basic to advance python tutorials will covered in this repo with detailed explanation of functions, input method, strings, loops, lists etc.
View ProjectXGBOOST-with-combination-of-factor.
July 12, 2018 – July 12, 2018
XGBoost (eXtreme Gradient Boosting) is an advanced implementation of gradient boosting algorithm.Xgboost is short for eXtreme Gradient Boosting package. The purpose of this Vignette is to show you how to use Xgboost to build a model and make predictions. It is an efficient and scalable implementation of gradient boosting framework by J. Friedman et al. (2000) and J. H. Friedman (2001). Two solvers are included: linear model ; tree learning algorithm. It supports various objective functions, including regression, classification and ranking. The package is made to be extendable, so that users are also allowed to define their own objective functions easily.
View ProjectQuick-Analysis-in-R-with-the-Iris-Dataset
April 16, 2018 – April 16, 2018
The Iris dataset is part of the datasets library. We can access it as a data frame by loading the library, that will also load the data frame by attach(iris) and analyse the data of iris.
View ProjectVisualisation-with-TensorBoard
March 22, 2018 – March 22, 2018
So what is TensorBoard and why would we want to use it? TensorBoard is a suite of web applications for inspecting and understanding your TensorFlow runs and graphs. TensorBoard currently supports five visualizations: scalars, images, audio, histograms, and graphs. The computations you will use in TensorFlow for things such as training a massive deep neural network, can be fairly complex and confusing, TensorBoard will make this a lot easier to understand, debug, and optimize your TensorFlow programs.
View ProjectBuilding-and-applying-a-logistic-regression-spam-model-in-R
March 11, 2018 – March 11, 2018
Evaluating Classification model A classification model places examples into two or more categories. The most common measure of classifier quality is accuracy and the incredible tool called the confusion matrix.
View ProjectExploratory-Data-Analysis-with-R
February 23, 2018 – April 3, 2018
Data Analysis on wine data. First we merge the data of red wine and white wine then start analysing it. We are going to use ggplot and ggthemes to plot the data, corrplot to find the correlation of variables, wine quality distribution and apply random forest model and variable importance.
View ProjectAudio-Mining-in-python
December 26, 2017 – December 26, 2017
In this repo I'm taking an audio file to generate its transcript by using Liv.ai API's. You can use any API or tools to generate transcript. On generated output I am going to do text mining.
View ProjectCultural Fit Analysis
The candidate's projects are primarily personal and academic in nature, focusing on exploring various data science concepts and tools. While this demonstrates initiative and a passion for the field, there is no information regarding collaborative projects, team environments, or contributions to open-source, which makes it difficult to assess cultural fit for a senior role requiring teamwork and broader impact. The projects are diverse in topics within data science, but lack real-world application or business context.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The candidate's project descriptions indicate a focus on technical implementation.