Pinned Repositories
2048_Python
Here I have developed one of the most famous single player game - 2048, by making the use of my Python 3 skills.
Automatic_License_Plate_Recognition
Face_Recognition_Attendance_System
MicrosoftMalwareDetection
==>>Problem Statement : In the past few years, the malware industry has grown very rapidly that, the syndicates invest heavily in technologies to evade traditional protection, forcing the anti-malware groups/communities to build more robust softwares to detect and terminate these attacks. The major part of protecting a computer system from a malware attack is to identify whether a given piece of file/software is a malware. ==>>Source/Useful Link : Microsoft has been very active in building anti-malware products over the years and it runs it’s anti-malware utilities over <b>150 million computers</b> around the world. This generates tens of millions of daily data points to be analyzed as potential malware. In order to be effective in analyzing and classifying such large amounts of data, we need to be able to group them into groups and identify their respective families. -> Source: https://www.kaggle.com/c/malware-classification
ML_Playground
On the way to ML
PersonalizedCancerPrediction_CaseStudy
Here I have tried to solve an problem by Quora, posted on Kaggle. Problem Statement :--A lot has been said during the past several years about how precision medicine and, more concretely, how genetic testing is going to disrupt the way diseases like cancer are treated. But this is only partially happening due to the huge amount of manual work still required. Memorial Sloan Kettering Cancer Center (MSKCC) launched this competition, accepted by the NIPS 2017 Competition Track, because we need your help to take personalized medicine to its full potential. Once sequenced, a cancer tumor can have thousands of genetic mutations. But the challenge is distinguishing the mutations that contribute to tumor growth (drivers) from the neutral mutations (passengers). Currently this interpretation of genetic mutations is being done manually. This is a very time-consuming task where a clinical pathologist has to manually review and classify every single genetic mutation based on evidence from text-based clinical literature. For this competition MSKCC is making available an expert-annotated knowledge base where world-class researchers and oncologists have manually annotated thousands of mutations. We need your help to develop a Machine Learning algorithm that, using this knowledge base as a baseline, automatically classifies genetic variations.
RNN_Music_generation
Here the shear power of RNN-LSTM is used to generate music completely new piece of folk music. Here ‘abc’ notation is used to represent the music in form of textual data.
Stackoverflow_Tag_Prediction
Problem Statemtent - Suggest the tags based on the content that was there in the question posted on Stackoverflow. Source-Kaggle(https://www.kaggle.com/c/facebook-recruiting-iii-keyword-extraction/) - This competition tests your text skills on a large dataset from the Stack Exchange sites. The task is to predict the tags (a.k.a. keywords, topics, summaries), given only the question text and its title. The dataset contains content from disparate stack exchange sites, containing a mix of both technical and non-technical questions.
Taxi_Prediction-CaseStudy
Vehicle_Object_Detection
Sahil-Chavan's Repositories
Sahil-Chavan/MicrosoftMalwareDetection
==>>Problem Statement : In the past few years, the malware industry has grown very rapidly that, the syndicates invest heavily in technologies to evade traditional protection, forcing the anti-malware groups/communities to build more robust softwares to detect and terminate these attacks. The major part of protecting a computer system from a malware attack is to identify whether a given piece of file/software is a malware. ==>>Source/Useful Link : Microsoft has been very active in building anti-malware products over the years and it runs it’s anti-malware utilities over <b>150 million computers</b> around the world. This generates tens of millions of daily data points to be analyzed as potential malware. In order to be effective in analyzing and classifying such large amounts of data, we need to be able to group them into groups and identify their respective families. -> Source: https://www.kaggle.com/c/malware-classification
Sahil-Chavan/ML_Playground
On the way to ML
Sahil-Chavan/RNN_Music_generation
Here the shear power of RNN-LSTM is used to generate music completely new piece of folk music. Here ‘abc’ notation is used to represent the music in form of textual data.
Sahil-Chavan/Stackoverflow_Tag_Prediction
Problem Statemtent - Suggest the tags based on the content that was there in the question posted on Stackoverflow. Source-Kaggle(https://www.kaggle.com/c/facebook-recruiting-iii-keyword-extraction/) - This competition tests your text skills on a large dataset from the Stack Exchange sites. The task is to predict the tags (a.k.a. keywords, topics, summaries), given only the question text and its title. The dataset contains content from disparate stack exchange sites, containing a mix of both technical and non-technical questions.
Sahil-Chavan/Vehicle_Object_Detection
Sahil-Chavan/2048_Python
Here I have developed one of the most famous single player game - 2048, by making the use of my Python 3 skills.
Sahil-Chavan/AdClickPrediction-CaseStudy
__ Introduction: Clickthrough rate (CTR) __ is a ratio showing how often people who see your ad end up clicking it. Clickthrough rate (CTR) can be used to gauge how well your keywords and ads are performing. - CTR is the number of clicks that your ad receives divided by the number of times your ad is shown: clicks ÷ impressions = CTR. For example, if you had 5 clicks and 100 impressions, then your CTR would be 5%. - Each of your ads and keywords have their own CTRs that you can see listed in your account. - A high CTR is a good indication that users find your ads helpful and relevant. CTR also contributes to your keyword's expected CTR, which is a component of Ad Rank. Note that a good CTR is relative to what you're advertising and on which networks. > Credits: Google (https://support.google.com/adwords/answer/2615875?hl=en) Search advertising has been one of the major revenue sources of the Internet industry for years. A key technology behind search advertising is to predict the click-through rate (pCTR) of ads, as the economic model behind search advertising requires pCTR values to rank ads and to price clicks. In this task, given the training instances derived from session logs of the Tencent proprietary search engine, soso.com, participants are expected to accurately predict the pCTR of ads in the testing instances.
Sahil-Chavan/Automatic_License_Plate_Recognition
Sahil-Chavan/Face_Recognition_Attendance_System
Sahil-Chavan/PersonalizedCancerPrediction_CaseStudy
Here I have tried to solve an problem by Quora, posted on Kaggle. Problem Statement :--A lot has been said during the past several years about how precision medicine and, more concretely, how genetic testing is going to disrupt the way diseases like cancer are treated. But this is only partially happening due to the huge amount of manual work still required. Memorial Sloan Kettering Cancer Center (MSKCC) launched this competition, accepted by the NIPS 2017 Competition Track, because we need your help to take personalized medicine to its full potential. Once sequenced, a cancer tumor can have thousands of genetic mutations. But the challenge is distinguishing the mutations that contribute to tumor growth (drivers) from the neutral mutations (passengers). Currently this interpretation of genetic mutations is being done manually. This is a very time-consuming task where a clinical pathologist has to manually review and classify every single genetic mutation based on evidence from text-based clinical literature. For this competition MSKCC is making available an expert-annotated knowledge base where world-class researchers and oncologists have manually annotated thousands of mutations. We need your help to develop a Machine Learning algorithm that, using this knowledge base as a baseline, automatically classifies genetic variations.
Sahil-Chavan/Taxi_Prediction-CaseStudy
Sahil-Chavan/Application-of-Object-Detection-CBIR-in-E-commerce-Fashion-Industry
Sahil-Chavan/Friend-Recommendation-System-Facebook-Using-GraphMining
This project is based on the problem statement provided by Facebook on kaggle -> https://www.kaggle.com/c/FacebookRecruiting/overview
Sahil-Chavan/Python-for-Data-Science-Coursera
Python for Data Science Coursera Course Fully Completed. Contains legitimate, efficient and best answers.
Sahil-Chavan/Qube_Health_Assignment
This is the implementation to the assignment provided by Qube Health.
Sahil-Chavan/Quora_CaseStudy
Here I have tried to solve an problem by Quora, posted on Kaggle. Problem Statement :-- Where else but Quora can a physicist help a chef with a math problem and get cooking tips in return? Quora is a place to gain and share knowledge about anything. It’s a platform to ask questions and connect with people who contribute unique insights and quality answers. This empowers people to learn from each other and to better understand the world. Over 100 million people visit Quora every month, so its no surprise that many people ask similarly worded questions. Multiple questions with the same intent can cause seekers to spend more time finding the best answer to their question, and make writers feel they need to answer multiple versions of the same question. Quora values canonical questions because they provide a better experience to active seekers and writers, and offer more value to both of these groups in the long term. Currently, Quora uses a Random Forest model to identify duplicate questions. In this competition, Kagglers are challenged to tackle this natural language processing problem by applying advanced techniques to classify whether question pairs are duplicates or not. Doing so will make it easier to find high quality answers to questions resulting in an improved experience for Quora writers, seekers, and readers.
Sahil-Chavan/Sahil-Chavan
My Profile
Sahil-Chavan/Task-Manager-NodeJS
Making an Task Manager App in Node JS
Sahil-Chavan/Weather_Forecast_App-NodeJS
Steps towards nodejs
Sahil-Chavan/weatherApp_Django