Pinned Repositories
triangle_sector_similarity
It takes two vectors as an input and prints and can return Cosine Similarity, Eucledian Distance, Triangle Area - Sector Area Similarity.
APS-FAILURE-OF-SCANIA
Prediction of Failures in the Air Pressure System of Scania Trucks
heart_disease_prediction
wns_challenge
100DaysOfCode
Codeshows 100DaysOfCode repository
AlgoExpert
The repo for my solutions of AlgoExpert problems
Amazon_fine_food_review
The Amazon Fine Food Reviews dataset consists of 568,454 food reviews. This dataset consists of a single CSV file, Reviews.csv
Chatbot-using-Recurrent-Neural-Networks
A conversational agent or a chatbot is piece of software which can communicate with human users with the help of natural language processing (NLP). Modelling conversation is a very crucial task in natural language processing and artificial intelligence (AI). Since the discovery of artificial intelligence, creating a good chatbot is one of the field’s hardest and complex challenges. Chatbots can be used for various tasks such as make phone calls, provide reminders etc; in general they have to understand users’ utterances and provide relevant responses for the problem in hand. Previously, methods which were used for constructing chatbot architectures relied on hand-written rules, templates or simple statistical methods. Rising and innovating field of deep learning have replaced previous models with trainable neural network models. The recurrent encoder-decoder model is the dominating model in the field modelling conversations. Multiple variations and features have been presented that have changed the quality of the conversation that chatbots are capable of. In our project, we have surveyed recent literatures published, examining various publications related to chatbots. We started with taking Cornell movie dialogue corpus as our dataset then after training our model with it and fine tuning it with various parameters, non-satisfactory results lead us to take another dataset and we trained and tested our final model on modified Gunthercox dataset which gave us satisfactory results for an open domain chatbot or general domain chatbot.
data-structures-algorithms-level-up-bootcamp
C++ Code Repository.
dlaicourse
Notebooks for learning deep learning
mohvam98's Repositories
mohvam98/fake_news_twitter
mohvam98/fake_news_classification
mohvam98/mohvam98.github.io
mohvam98/triangle_sector_similarity
It takes two vectors as an input and prints and can return Cosine Similarity, Eucledian Distance, Triangle Area - Sector Area Similarity.
mohvam98/data-structures-algorithms-level-up-bootcamp
C++ Code Repository.
mohvam98/python-data-science-mastercourse
Python for data science mastercourse
mohvam98/Image-Captioning
mohvam98/practical-statistics-for-data-scientists
Code repository for O'Reilly book
mohvam98/monk_v1
Monk is a low code Deep Learning tool and a unified wrapper for Computer Vision.
mohvam98/ml-bot
mohvam98/dlaicourse
Notebooks for learning deep learning
mohvam98/100DaysOfCode
Codeshows 100DaysOfCode repository
mohvam98/AlgoExpert
The repo for my solutions of AlgoExpert problems
mohvam98/interview-prep-cpp
My solutions to coding interview problems on Leetcode, Algoexpert, Codewars and other interview preparation websites
mohvam98/wns_challenge
mohvam98/python
mohvam98/predict-traffic-volume
mohvam98/heart_disease_prediction
mohvam98/APS-FAILURE-OF-SCANIA
Prediction of Failures in the Air Pressure System of Scania Trucks
mohvam98/Chatbot-using-Recurrent-Neural-Networks
A conversational agent or a chatbot is piece of software which can communicate with human users with the help of natural language processing (NLP). Modelling conversation is a very crucial task in natural language processing and artificial intelligence (AI). Since the discovery of artificial intelligence, creating a good chatbot is one of the field’s hardest and complex challenges. Chatbots can be used for various tasks such as make phone calls, provide reminders etc; in general they have to understand users’ utterances and provide relevant responses for the problem in hand. Previously, methods which were used for constructing chatbot architectures relied on hand-written rules, templates or simple statistical methods. Rising and innovating field of deep learning have replaced previous models with trainable neural network models. The recurrent encoder-decoder model is the dominating model in the field modelling conversations. Multiple variations and features have been presented that have changed the quality of the conversation that chatbots are capable of. In our project, we have surveyed recent literatures published, examining various publications related to chatbots. We started with taking Cornell movie dialogue corpus as our dataset then after training our model with it and fine tuning it with various parameters, non-satisfactory results lead us to take another dataset and we trained and tested our final model on modified Gunthercox dataset which gave us satisfactory results for an open domain chatbot or general domain chatbot.
mohvam98/Near-Duplicate-Video-Detection
Detecting near-duplicate videos by aggregating features from intermediate CNN layers
mohvam98/Amazon_fine_food_review
The Amazon Fine Food Reviews dataset consists of 568,454 food reviews. This dataset consists of a single CSV file, Reviews.csv