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24 search results found
Amazing Feature Engineering
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485
Feature engineering is the process of using domain knowledge to extract features from raw data via data mining techniques. These features can be used to improve the performance of machine learning algorithms. Feature engineering can be considered as applied machine learning itself.
Datasist
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137
A Python library for easy data analysis, visualization, exploration and modeling
Datacon
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49
🏆DataCon大数据安全分析大赛,2019年方向二(恶意代码检测)冠军源码、2020年方向五(恶
Data Science Regular Bootcamp
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39
Regular practice on Data Science, Machien Learning, Deep Learning, Solving ML Project problem, Analytical Issue. Regular boost up my knowledge. The goal is to help learner with learning resource on Data Science filed.
Drugs Recommendation Using Reviews
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27
Analyzing the Drugs Descriptions, conditions, reviews and then recommending it using Deep Learning Models, for each Health Condition of a Patient.
Data Science End To End
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22
A Respository to get you job ready as a Data Scientist
Fifa 2019 Analysis
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21
This is a project based on the FIFA World Cup 2019 and Analyzes the Performance and Efficiency of Teams, Players, Countries and other related things using Data Analysis and Data Visualizations
Hdb_resale_prices
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18
Predicted and identified the drivers of Singapore HDB resale prices (2015-2019) with 0.96 Rsquare & $20,000 MAE. Web app deployment using Streamlit for user price prediction.
Bubble_plot
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18
Visualize linear and non-linear connections between numerical/categorical features (2D histogram with bubbles)
Data Science
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17
Utilizing Kaggle Data and Real-World Data for Data Science and Prediction in Python, R, Excel, Power BI, and Tableau.
World Food Production
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14
Comparing Top food and feed Producers around the globe and also seeking some interesting answers, solutions, patterns, hints and warnings through the power of Data Analysis and Data Visualization using Machine Learning.
Exemplary Ml Pipeline
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14
Exemplary, annotated machine learning pipeline for any tabular data problem.
Titanic Survival In Depth Analysis
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12
Used Pandas , Matplotlib , Seaborn libraries to Analyze , Visualize and Explore the data of people travelling on Titanic, and Used Scikit-learn Modelling Algorithms to predict their probability of Survival.
Data_analysis
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12
Notebooks on some of the past data analysis and data science projects I've done
Diamonds In Depth Analysis
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12
Given dataset of Diamonds with features such as Cut, Carat, Clarity etc. I have used libraries such as Pandas, Numpy, Matplotlib, Seaborn to Analyse and Estimate the Price of Diamonds based on the features. Using Scikit-Learn , implemented Algorithms to increase the effective R2 score.
Black Friday Regression Analysis
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9
Predicting Prices for the products to be sold on Black Friday in US using Regression Analysis, Feature Engineering, Feature Selection, Feature Extraction and Data analysis - Data Visualizations.
Google Job Skills
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9
Having an Exploratory Analysis at what kind of Jobs and Job Locations are provided by Google and Youtube, also we look into some specific details which are important to get hired by youtube and google.
Avito Demand Prediction Challenge
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7
It is a Competition for Regression Challenge held by Kaggle, It is based on a Avito Dataset whose size is 123GB which can be accessed from Kaggle, I have done Data Pre-processing, feature engineering, feature extraction, data visualization, machine learning, stacking and boosting
Kaggle
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7
Kaggle Courses - All Exercises of the respective courses.
Pakistan Suicide Bombing Dataset
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6
Analyzing the Suicide Bombing Patterns and seeking some of the most tangled questions with good visualizations with the help of Machine Learning and Data Science.
Stravakudos
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6
🏃 🎯 Predicting Strava Kudos on my own activities using the given activity's attributes.
Data Scientist
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6
A Minimalist RoadMap to the Data Science World
Introduction To Data Analyst And Data Science
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6
Introduction to Data Analyst and Data Science for Beginners
Careercon Robots Need Help
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6
It is Data Science and Machine Learning Competition Hosted by Kaggle where we have to perform multi-class classification on the labels, a very good amount of feature engineering, data preprocessing, data visualizations and modelling is done on the data set to get a good accuracy using random forest and xg boost classifier
Goodbooks Recommender
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5
Build a Book Recommendation System using Goodreads data (10k books)
Titanic Passenger Survival Prediction
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5
Using Classification Techniques, Data reprocessing, Feature Engineering, Feature Extraction and Classification Algorithms from Machine Learning to Predict who can Survive the attack of Tsunami.
Loan Default Prediction
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5
L&T Financial Services & Analytics Vidhya presents ‘DataScience FinHack’. where I have predicted whether the customer will be defaulter in the first EMI payment using different algorithms from machine learning
Related Searches
Datavisualization Data Visualization (7,481)
Jupyter Notebook Data Visualization (1,985)
Python Data Visualization (1,377)
Javascript Data Visualization (1,003)
Machine Learning Data Visualization (588)
1-24 of 24 search results
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