akashmavle5 Goto Github PK

followers: 6.0 following: 4.0 repos: 573.0 gists: 2.0

Type: User

akashmavle5's Projects

hands-on-question-answering-systems-bert

Source Code for 'Hands-on Question Answering Systems with BERT' by Navin Sabharwal and Amit Agrawal

hands-on-reinforcement-learning-with-python

Hands-On Reinforcement Learning with Python, published by Packt

hands-on-supervised-machine-learning-with-python

Hands-on Supervised Machine Learning with Python, Published by Packt

health-insurance-cross-sell-eda-and-machine-learning-modeling

This is a note book of exploratory data analysis on cross selling of health insurance customers on vehicle insurance product and using machine learning to predict whether a customer is interested or not in vehicle insurancen

healthcare_ml

A curated list of ML|NLP resources for healthcare.

hedge-fund-stock-market-analysis

Developed a deep learning model that allows trading firms to analyze large patterns of stock market data and look for possible permutations to increase returns and reduce risk. Trained the model using a Multilayer Perceptron Neural Network on a vast set of features that influence the stock market indices. Performed technical analysis using historical stock prices and fundamental analysis using social media dat

hol-azure-machine-learning

Introduction to Machine Learning and Azure Machine Learning Services. Hands on labs to show Azure Machine Learning features, developing experiments, feature engineering, R and Python Scripting, Production stage, publishing models as web service, RRS and BES usage

horovod

Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.

hudi

Upserts, Deletes And Incremental Processing on Big Data.

hyperparameter-optimization-of-machine-learning-algorithms

Implementation of hyperparameter optimization/tuning methods for machine learning & deep learning models (easy&clear)

identifying-potential-customers-for-loans

Supervised Learning Identified potential loan customers for Thera Bank using classification

identifying-potential-customers-for-loans-1

Identified potential loan customers for Thera Bank using classification techniques. Compared models built with Logistic Regression and KNN algorithm in order to select the best performing one.

ifrs9

The full scope of IFRS 9 Impairment models including PD, LGD and EAD are provided. It also covers ECL, which is the combination of those three parameters as well as staging criteria.

igel

a delightful machine learning tool that allows you to train, test and use models without writing code

image2text

:clipboard: Python wrapper to grab text from images and save as text files using Tesseract Engine

image2text-1

A deep learning project to tell a story with an image or a video.

imp

Predict time needed to resolve incidents, and practice feature engineering, Linear Regression and RFs.

incident-impact-prediction

Predicting the incidents raised by the customer

incubator-superset

Apache Superset is a Data Visualization and Data Exploration Platform

insurance-claim-prediction

In this Data set we are Predicting the Insurance Claim by each user, Machine Learning algorithms for Regression analysis are used and Data Visualization are also performed to support Analysis.