Kolluboyina Trinadh – Junior Data scientist

About Me

“Aspiring Data Scientist eager to contribute to team success through hard work, attention to detail and excellent organizational skills. Clear understanding of analysis of Data, Data modelling and coming with solid mathe…

Experience

Junior Data scientist

Netwerk Ai Pvt Ltd, Bangalore

Sep 2022 - Present · 3 years 10 months

Project: State wise stock market sentiment analysis using web scraping and Key BERT
The project focus on the sentiment of people (customers) in different regions towards the stock market.
Our client decides the contents of advertisements based on the sentiments type by the input we give from our analysis methods.
A large data is collected through web scraping via platforms like blogs, public websites, social media comments few other sources using certain key words like stock_market_fraud, stock_learning etc with profile location.
The data is collected in .txt format.
This data is cleaned & given as input to the KeyBERT and WordCloud algorithm.
This model will gives us the perspective region & its sentiment.
A set of 45 different combinations are made run to collect the data.
The end result is a list of keywords that can be used for state-wise sentiment analysis of the stock market for social media marketing and advertisements.
Extracting data from web scraping.
Combining the keywords with the region and platforms.
Collecting the data from .txt file.
The cleaning process done by removing the pronouns, verbs, breaking conjunctions.
The cycle was run for 25days & 5days buffer to validate any platform change.
Working with NLP algorithm KeyBERT to get the keywords data region wise with different platforms.
Working with WordCloud algorithm to get the visual representation of the frequency of the keyword.

Data scientist

Netzwerk Ai pvt Ltd

Sep 2022 - Present · 3 years 10 months

Strong Mathematical foundation and good in Statistics, Probability.
 Experience of Machine learning algorithms like Simple Linear Regression,
Multiple Regression, Polynomial Regression, Logistic Regression, SVM, kNN,
Naive Bayes, Decision Tree, Random Forest, AdaBoost, Gradient Boosting,
XGBoost, K-fold cross validation, Grid and Random Search.
 Skilled in Minimizing the cost function based algorithms like: Gradient
Descent, Stochastic Gradient Descent and Batch Gradient Descent.
 Good knowledge of Clustering algorithms like K means, Agglomerative
Hierarchical Clustering, Divisive Hierarchical Clustering,and
Dimensionality Reduction like PCA, LDA.
 Hyper parameter tuning using Grid Search, Random Search.
 Performing Exploratory Data Analysis(EDA) on Raw data.
 Feature Engineering in Python – Missing value treatment, outlier handling,
data transformation, Feature Selection and reshaping data using Python
packages like Numpy, Pandas and Scikit Learn.
 Data Visualization techniques with help of Matplotlib, Seaborn and Tableau.
 Good knowledge of Deep Learning (DL) and hands-on with Neural Networks,
Loss Function, Cost Function, Optimizers, Artificial Neural Networks (ANN),
Convolutional Neural Networks (CNN) and Recurrent Neural Networks
(RNN), LSTM, Generative AI.
 Skilled in libraries like Numpy, Pandas, Matplotlib, Seaborn, Scikit Learn,
Tensorflow, Keras, OpenCV and NLTK.
 Basic Understanding of Computer Vision techniques like Image pre-
processing, Image Segmentation, Object detection, Object recognition,
Object tracking.
 Advance Understanding of Natural Language Processing (NLP)
techniques like tokenization, stemming, lemmatization, Text
Analysis, Matrix TFIDF and word2vec.
 Self-motivated team player with good communication and presentation skills
 Good analytical and problem solving skills

Skills

Python MySQL Matplotlib Seaborn Tableau Anaconda Jupyter Notebook Google Colab Spyder IDE PyCharm Windows XP Windows 10 KeyBERT pytesseract Chrome Driver Selenium WordCloud Statistics Probability Simple Linear Regression Multiple Regression Polynomial Regression Logistic Regression SVM kNN Naive Bayes Decision Tree Random Forest AdaBoost Gradient Boosting XGBoost K-fold cross validation Grid Search Random Search Gradient Descent Stochastic Gradient Descent Batch Gradient Descent K-means Agglomerative Hierarchical Clustering Divisive Hierarchical Clustering PCA LDA EDA Feature Engineering NumPy Pandas Scikit Learn TensorFlow Keras OpenCV