Logistic Encoder

Anwoy Panigrahi

Email: admcxu@r.postjobfree.com Github: https://github.com/Anwoy-p

LinkedIn: https://www.linkedin.com/in/anwoy-panigrahi-415754169/

+91-958*******

Bangalore, India

Technical Expertise

• Deep understanding and expertise in the field of Machine Learning, Deep Learning and Statistical Learning.

• Expertise in Exploratory Data Analysis and Data Visualization with principal component analysis and TSNE

• Graphs, Classification, Regression, Computer Vision and Deep Learning (MLP, CNN, RNN – Encoder- Decoder Attention Model )

• Natural Language Processing Transformer (BERT)

• Mathematical knowledge in Optimization techniques – Gradient Decent, SGD, AdaGrad, AdaDelta and Adam

• Linear and Nonlinear models, Bayesian theory, Recommendation systems, Data visualization.

• KNN, Logistic Regression, Linear Regression, SVM, Naïve Bayes, Random forest, Decision Tree, XGBoost,Gradient Boosting Decision Trees.

Core Competencies

Programming Languages: Python

Database: MySQL

IDE/Tools: Jupyter Notebook

Machine Learning Tools scikit-learn, Tensor Flow, Keras, transformers, OpenCV, Pandas, Numpy

Projects Details

Predicting the next month sale of a given shop-item pair Objective: - The goal of this project is to predict the future sales for a give shop-item pair using Machine Learning Technique.

Analysis: - Performed Univariate Analysis on the different attributes of Sales Dataset, Coming off with some new features to increase the performance of the model. Models built: - Custom ensemble, Logistic Regression, Linear Support Vector Machine, XGBoost, DNN, Random Forest,,Decision tree to Predict the future sales. Framework & Lib:- Python – SkLearn, Ensemble, XGBoost, Decision Tree, Matplotlib, Numpy, Pandas, Tensor Flow, Keras.

Blog on Predict Future Sales: - https://medium.com/analytics-vidhya/can-machine-predict-sales- 4e9bc17e3786

Detecting eye condition from retina scanned images Objective: - The goal of this project is to detect severity of diabetic retinopathy from retina scan images using transfer learning.

Analysis: - Using up-sampling to deal with data imbalance then using Thresholding to detect irregularities present in an image.

Models built: - CNN, Vgg16, EfficientNetB3, ResNet50, Combination of Vgg16, ResNet50 and EfficientNetB3 to predict diabetic retinopathy.

Framework & Lib:- Python – Convolution Neural Network, OpenCV, Tensor Flow, Keras, Matplotlib, Numpy, Pandas

Blog Link: https://medium.com/analytics-vidhya/black-blind-or-not-8897e6c1ad4c Educational Qualification

2019 BTech with specialization in Information and Technology engineering from College of Engineering and Technology, Bhubaneswar With [7.8 CGPA].

2015 12th from Kendriya Vidyalaya Baripada with 90.2%. 2013 10th from Kendriya Vidyalaya Baripada [CGPA 10]. Certification

• Machine Learning certified in Applied AI .

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