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Saurabh Rai
Delhi, India
CodersRank Score
What is this?
This represents your current experience. It calculates by analyzing your connected repositories. By measuring your skills by your code, we are creating the ranking, so you can know how good are you comparing to another developers and what you have to improve to be better
Information on how to increase score and ranking details you can find in this blog post.
436.1
CodersRank Rank
Top 2%
Associate
Developer
Java
Top 100
Pandas
Developer
India
Top 10
Streamlit
Developer
India
Highest experience points: 0 points,
0 activities in the last year
Jupyter Notebook
37.9
exp.
Python
46
exp.
JSON
49.8
exp.
Java
67.3
exp.
C++
18.5
exp.
HTML
63.6
exp.
CSS
64.2
exp.
JavaScript
40.9
exp.
TypeScript
19.3
exp.
SCSS
18.6
exp.
Less
7
exp.
List your work history, including any contracts or internships
BeyondAlphabets
Jun 2020 - Aug 2020 (2 months)
Software Engineer Intern
Software Developer Intern, developed a NLP based Text Similarity Model to compare Resumes with Job Description and speed up the hiring process, and reduce bias while selecting candidates.
- Resumes were scraped from Resdex's free resume search (personal data redacted before use)
- With the help of textract, all the resume's and job description were extracted and preprocessed using NLTK, Spacy and Gensim library.
- For LDA, and Topic Modelling, Gensim's TF-IDF and LDA implementation was applied.
- However another approach using Gensim's Word2Vec and Cosine Similarity was used, but due to the time taken for creating document specific vectors for each resume vs. the resources available, it was not implemented.
- Rest of the project is presented in the form of a Dashboard using Streamlit.io and Plotly's Graphing Library.
- Resumes were scraped from Resdex's free resume search (personal data redacted before use)
- With the help of textract, all the resume's and job description were extracted and preprocessed using NLTK, Spacy and Gensim library.
- For LDA, and Topic Modelling, Gensim's TF-IDF and LDA implementation was applied.
- However another approach using Gensim's Word2Vec and Cosine Similarity was used, but due to the time taken for creating document specific vectors for each resume vs. the resources available, it was not implemented.
- Rest of the project is presented in the form of a Dashboard using Streamlit.io and Plotly's Graphing Library.
Add some compelling projects here to demonstrate your experience
Object Detection using Transferred Learning
Oct 2019 - Oct 2019
Object Detection of Images using the ResNet50 model.
The Original ResNet50 weights were used and then trained over Stanford 256 Objects Dataset, while maintaining accuracy. This was trained over Tensorflow GPU.
The Original ResNet50 weights were used and then trained over Stanford 256 Objects Dataset, while maintaining accuracy. This was trained over Tensorflow GPU.
Fruit Detection using Convolution Neural Networks in Keras, Tensorflow-GPU
Sep 2019 - Sep 2019
Trained a Convolutional Neural Network Model to predict fruits of over 100+ Classes (types) with a training accuracy of over 95%, and testing accuracy of over 90%. The model was trained over a huge dataset of 80,000 + Images and was trained and tested over Tensorflow running on GPU.
Naive Resume Matching
Text Similarity Measure applied to Resumes and Job Descriptions.
This section lets you add any degrees or diplomas you have earned.
Guru Gobind Singh Indraprastha University
Bachelor's degree, Computer Science
Dec 2016 - Dec 2020
Tensorflow 2.0: Deep Learning and Artificial Intelligence
Apr 2020
Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning
Jun 2020
Machine Learning
Apr 2019