Machine Learning Workflow With PythonThis is a comprehensive ML techniques with python: Define the Problem- Specify Inputs & Outputs- Data Collection- Exploratory data analysis -Data Preprocessing- Model Design- Training- Evaluation
Stars: ✭ 157 (+375.76%)
Mutual labels: kaggle, feature-extraction, kaggle-competition, feature-engineering
Kaggle CompetitionsThere are plenty of courses and tutorials that can help you learn machine learning from scratch but here in GitHub, I want to solve some Kaggle competitions as a comprehensive workflow with python packages. After reading, you can use this workflow to solve other real problems and use it as a template.
Stars: ✭ 86 (+160.61%)
Mutual labels: kaggle, feature-extraction, kaggle-competition, feature-engineering
fastknnFast k-Nearest Neighbors Classifier for Large Datasets
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Mutual labels: kaggle, feature-extraction, feature-engineering
Data-ScienceUsing Kaggle Data and Real World Data for Data Science and prediction in Python, R, Excel, Power BI, and Tableau.
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Mutual labels: kaggle, datascience, feature-engineering
The Data Science WorkshopA New, Interactive Approach to Learning Data Science
Stars: ✭ 126 (+281.82%)
Mutual labels: random-forest, datascience, feature-engineering
ChefboostA Lightweight Decision Tree Framework supporting regular algorithms: ID3, C4,5, CART, CHAID and Regression Trees; some advanced techniques: Gradient Boosting (GBDT, GBRT, GBM), Random Forest and Adaboost w/categorical features support for Python
Stars: ✭ 176 (+433.33%)
Mutual labels: random-forest, kaggle, decision-trees
50-days-of-Statistics-for-Data-ScienceThis repository consist of a 50-day program. All the statistics required for the complete understanding of data science will be uploaded in this repository.
Stars: ✭ 19 (-42.42%)
Mutual labels: feature-extraction, feature-engineering
StoreItemDemand(117th place - Top 26%) Deep learning using Keras and Spark for the "Store Item Demand Forecasting" Kaggle competition.
Stars: ✭ 24 (-27.27%)
Mutual labels: kaggle, kaggle-competition
Statistical-Learning-using-RThis is a Statistical Learning application which will consist of various Machine Learning algorithms and their implementation in R done by me and their in depth interpretation.Documents and reports related to the below mentioned techniques can be found on my Rpubs profile.
Stars: ✭ 27 (-18.18%)
Mutual labels: datascience, decision-trees
digit recognizerCNN digit recognizer implemented in Keras Notebook, Kaggle/MNIST (0.995).
Stars: ✭ 27 (-18.18%)
Mutual labels: kaggle, kaggle-competition
Data-Science-Hackathon-And-CompetitionGrandmaster in MachineHack (3rd Rank Best) | Top 70 in AnalyticsVidya & Zindi | Expert at Kaggle | Hack AI
Stars: ✭ 165 (+400%)
Mutual labels: kaggle, kaggle-competition
Orange3🍊 📊 💡 Orange: Interactive data analysis
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Mutual labels: random-forest, decision-trees
kaggle-berlinMaterial of the Kaggle Berlin meetup group!
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Mutual labels: kaggle, feature-engineering
argus-tgs-saltKaggle | 14th place solution for TGS Salt Identification Challenge
Stars: ✭ 73 (+121.21%)
Mutual labels: kaggle, kaggle-competition
dku-kaggle-class단국대 SW중심대학 2020년도 오픈소스SW설계 - 캐글뽀개기 수업 일정 및 강의자료
Stars: ✭ 48 (+45.45%)
Mutual labels: kaggle, datascience
tsflexFlexible time series feature extraction & processing
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Mutual labels: feature-extraction, feature-engineering
R-stats-machine-learningMisc Statistics and Machine Learning codes in R
Stars: ✭ 33 (+0%)
Mutual labels: random-forest, decision-trees
KaggleKaggle Kernels (Python, R, Jupyter Notebooks)
Stars: ✭ 26 (-21.21%)
Mutual labels: kaggle-competition, kaggle-dataset