Pinned Repositories
2017-slides
Slides and talk assets from PyCon 2017
30-seconds-of-python
Short Python code snippets for all your development needs
Analytics-Vidhya-India-ML-Hiring-Hackathon-2019
Loan Delinquency Prediction For Upcoming Month.#Evaluation:- Submissions are evaluated on F1-Score between the predicted class and observed. #F1-Score:- 0.35 #Rank 8 On Public Leaderboard
Brent-Oil-Price-Forecasting
The aim of this dataset and work is to predict future Crude Oil Prices based on the historical data available in the dataset. The data contains daily Brent oil prices from 17th of May 1987 until the 25th of February 2020.
Complex_Networks
A large number of real-world systems like Facebook, air-transport, metabolic reactions inside a living cell, and the Internet can be modelled as networks. Also several phenomena like traffic jams, rumour spreading and genetic regulations can be modelled as processes on networks making it an indispensable tool to study ‘complex systems’.
Deep_Learning
Deep learning is a subset of machine learning in artificial intelligence (AI) that has networks capable of learning unsupervised from data that is unstructured or unlabeled. Also known as deep neural learning or deep neural network.
Machine_Learning
Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. Machine learning focuses on the development of computer programs that can access data and use it learn for themselves.
Machine_Learning_Competition
Competition is a great first challenge to get started. This repository contains different participated competition codes & description.
Modeling_And_Simulation
Mathematical Modeling And Simulation
Stochastic_Optimization
Stochastic optimization methods are optimization methods that generate and use random variables. For stochastic problems, the random variables appear in the formulation of the optimization problem itself, which involves random objective functions or random constraints.
mangeshksagar's Repositories
mangeshksagar/Analytics-Vidhya-India-ML-Hiring-Hackathon-2019
Loan Delinquency Prediction For Upcoming Month.#Evaluation:- Submissions are evaluated on F1-Score between the predicted class and observed. #F1-Score:- 0.35 #Rank 8 On Public Leaderboard
mangeshksagar/Brent-Oil-Price-Forecasting
The aim of this dataset and work is to predict future Crude Oil Prices based on the historical data available in the dataset. The data contains daily Brent oil prices from 17th of May 1987 until the 25th of February 2020.
mangeshksagar/Complex_Networks
A large number of real-world systems like Facebook, air-transport, metabolic reactions inside a living cell, and the Internet can be modelled as networks. Also several phenomena like traffic jams, rumour spreading and genetic regulations can be modelled as processes on networks making it an indispensable tool to study ‘complex systems’.
mangeshksagar/2017-slides
Slides and talk assets from PyCon 2017
mangeshksagar/30-seconds-of-python
Short Python code snippets for all your development needs
mangeshksagar/Deep_Learning
Deep learning is a subset of machine learning in artificial intelligence (AI) that has networks capable of learning unsupervised from data that is unstructured or unlabeled. Also known as deep neural learning or deep neural network.
mangeshksagar/Machine_Learning
Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. Machine learning focuses on the development of computer programs that can access data and use it learn for themselves.
mangeshksagar/Machine_Learning_Competition
Competition is a great first challenge to get started. This repository contains different participated competition codes & description.
mangeshksagar/Modeling_And_Simulation
Mathematical Modeling And Simulation
mangeshksagar/Stochastic_Optimization
Stochastic optimization methods are optimization methods that generate and use random variables. For stochastic problems, the random variables appear in the formulation of the optimization problem itself, which involves random objective functions or random constraints.
mangeshksagar/amazon-sagemaker-examples
Example notebooks that show how to apply machine learning, deep learning and reinforcement learning in Amazon SageMaker
mangeshksagar/awesome-mlops
A curated list of references for MLOps
mangeshksagar/aws-modern-application-workshop
A tutorial for developers that want to learn about how to build modern applications on top of AWS. You will build a sample website that leverages infrastructure as code, containers, serverless code functions, CI/CD, and more.
mangeshksagar/data-engineer-roadmap
Roadmap to becoming a data engineer in 2021
mangeshksagar/data-science-from-scratch
code for Data Science From Scratch book
mangeshksagar/javascript-in-one-pic
Learn javascript in one picture.
mangeshksagar/machine_learning_complete
mangeshksagar/msds621
Course notes for MSDS621 at Univ of San Francisco, introduction to machine learning
mangeshksagar/notebook
Jupyter Interactive Notebook
mangeshksagar/numerical-mooc
A course in numerical methods with Python for engineers and scientists: currently 5 learning modules, with student assignments.
mangeshksagar/pandas
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
mangeshksagar/Petrophysics-Python-Series
A series of Jupyter notebooks showing how to load well log and petrophysical data in python.
mangeshksagar/Predictive_Maintenance
This repository demonstrates the steps in building a predictive maintenance solution.
mangeshksagar/python3-in-one-pic
Learn python3 in one picture.
mangeshksagar/scikit-learn
scikit-learn: machine learning in Python
mangeshksagar/solution-architecture-patterns
Reusable, vendor-neutral, industry-specific, vendor-specific solution architecture patterns for enterprise
mangeshksagar/Time-Series-Analysis
mangeshksagar/Transfer-Learning-in-keras---custom-data
Implementing Transfer Learning for custom data using VGG-16 and Resnet-50