My Studies on Kaggle

It is the repo I listed my kernels in Kaggle. You can access it in detail from my Kaggle address https://www.kaggle.com/bulentsiyah. (updated:13/06/2020)

Time Series Forecasting and Analysis

https://www.kaggle.com/bulentsiyah/time-series-forecasting-and-analysis-part-2

Content

• Deep Learning for Time Series Forecasting - (RNN)
• Multivariate Time Series with RNN
• Use Facebook's Prophet Library for forecasting

Deep Learning based Semantic Segmentation | Keras

https://www.kaggle.com/bulentsiyah/deep-learning-based-semantic-segmentation-keras

Content

• What is semantic segmentation
• Implementation of Segnet, FCN, UNet , PSPNet and other models in Keras
• I extracted Github codes

Learn OpenCV by Examples - with Python

https://www.kaggle.com/bulentsiyah/learn-opencv-by-examples-with-python

Content

• Sharpening
• Thresholding, Binarization & Adaptive Thresholding
• Dilation, Erosion, Opening and Closing
• Edge Detection & Image Gradients
• Perpsective Transform
• Scaling, re-sizing and interpolations
• Image Pyramids
• Cropping
• Blurring
• Contours
• Approximating Contours and Convex Hull
• Identifiy Contours by Shape
• Line Detection - Using Hough Lines
• Counting Circles and Ellipses
• Finding Corners
• Finding Waldo
• Background Subtraction Methods
• Funny Mirrors Using OpenCV

Plant Disease Using Siamese Network - Keras

https://www.kaggle.com/bulentsiyah/plant-disease-using-siamese-network-keras

One-shot Image Recognition

People may ask why have they used One-shot image recognition method though there are other state of art models like CNN and Hierarchical Bayesian Program Learning. The main reason for people using this method is the lack of data. The state of art Machine Learning Algorithms work very well when there is a huge amount of data but can fail miserably if there is a data scarcity.

Heart Disease Prediction using Neural Networks

https://www.kaggle.com/bulentsiyah/heart-disease-prediction-using-neural-networks

Classifying DNA Sequences-Markov Models-KNN-SVM

https://www.kaggle.com/bulentsiyah/classifying-dna-sequences-markov-models-knn-svm

Pima Dataset-Deep Learning Grid Search 84.4%

https://www.kaggle.com/bulentsiyah/pima-dataset-deep-learning-grid-search-84-4

Dogs vs. Cats Classification (VGG16 Fine Tuning)

https://www.kaggle.com/bulentsiyah/dogs-vs-cats-classification-vgg16-fine-tuning

RNN Basic-Gated RecurrentUnit-Sentiment Analysis

https://www.kaggle.com/bulentsiyah/rnn-basic-gated-recurrentunit-sentiment-analysis

Basic RNN-Long Short Term Memory(LSTMs)

https://www.kaggle.com/bulentsiyah/rnn-basic-long-short-term-memory-lstms

NLP Basics (NLTK-SkipGram-CBOW-Reg.Exp.-Stemmer)

https://www.kaggle.com/bulentsiyah/nlp-basics-nltk-skipgram-cbow-reg-exp-stemmer

Content

• StopWords - Stemmer - Count Vectorizer
• Reg.Exp.- Lemmatization - Bag of Words
• NLTK - Word2Vec(SkipGram,CBOW) - Glove

MNIST for beginners tensorflow DNN CNN keras

https://www.kaggle.com/bulentsiyah/mnist-for-beginners-tensorflow-dnn-cnn-keras

Keras-Deep Learning to Solve Titanic

https://www.kaggle.com/bulentsiyah/keras-deep-learning-to-solve-titanic

Comparing Classification-Clustering-Regression ML

https://www.kaggle.com/bulentsiyah/comparing-classification-clustering-regression-ml

Content

• Comparing Classification Methods
  • Logistic Regression Classification
  • K-Nearest Neighbour (KNN) Classification
  • SVM Classification
  • Naive Bayes Classification
  • Decision Tree Classification
  • Random Forest Classification
• Comparing Clustering Methods K-Means-Hierarchical
  • K-Means Clustering
  • Hierarchical Clustering
• Comparing Regression Methods
  • Linear Regression
  • Polynomial Regression
  • Support Vector Regression , Scaling
  • Decision Tree
  • Random Forest

Data Science and Visualization Exercise

https://www.kaggle.com/bulentsiyah/data-science-and-visualization-exercise

Content

• Cleaning Data
  • Diagnose data for cleaning
  • Exploratory data analysis (EDA)
  • Visual exploratory data analysis
  • Tidy data
  • Pivoting data
  • Concatenating data
  • Data types
  • Missing data and testing with assert
• Manipulating Data Frames with Pandas
  • Index objects and labeled data
  • Hierarchical indexing
  • Pivoting data frames
  • Stacking and unstacking data frames
  • Melting data frames
  • Categoricals and groupby
• Seaborn
  • Bar Plot
  • Point Plot
  • Joint Plot
  • Pie Plot
  • Lm Plot
  • Kde Plot
  • Violin Plot
  • Heatmap
  • Box Plot
  • Swarm Plot
  • Pair Plot
  • Count Plot
• Plotly
  • Line Plot
  • Scatter Plot
  • Bar Plot
  • Pie Plot
  • Bubble Plot
  • Histogram
  • Word Cloud
  • Box Plot
  • Scatter Plot Matrix
  • Inset Plot
  • 3D Scatter Plot
  • Multiple Subplots
  • Animation Plot Visualization Tools
  • Parallel Plots (Pandas)
  • Network Charts (networkx)
  • Venn Diagram (matplotlib)
  • Donut Plot (matplotlib)
  • Spyder Chart (matplotlib)
  • Cluster Map (seaborn)

Machine Learning Exercise

https://www.kaggle.com/bulentsiyah/machine-learning-exercise

Content

• Regression
  • Linear Regression
  • Multiple Linear Regression
  • Polynomial Linear Regression
  • Support Vector Regression
  • Decision Tree Regression
  • Random Forest Regression
• Classification
  • K-Nearest Neighbour (KNN) Classification
  • Support Vector Machine (SVM) Classification
  • Naive Bayes Classification
  • Decision Tree Classification
  • Random Forest Classification
• Clustering
  • K-Means Clustering
  • Hierarchical Clustering
• Other Content
  • Natural Language Process (NLP)
  • Principal Component Analysis (PCA)
  • Model Selection
  • Recommendation Systems

Python Exercise

https://www.kaggle.com/bulentsiyah/python-exercise

Content

• Python Basics
  • variable
  • user defined functions
  • default ve flexible functions
  • lambda function
  • nested function
  • anonymous function
  • list
  • tuple
  • dictionary
  • conditionals
  • loops
• Object Oriented Programming
  • class
• Numpy
  • basic operations
  • indexing and slicing
  • shape manipulation
  • convert and copy
• Pandas
  • indexing and slicing
  • filtering
  • list comprehension
  • drop and concatenating
  • transforming data
  • iteration example
  • zip example
  • example of list comprehension
• Visualization with Matplotlib
  • line Plot example
  • scatter plot
  • histogram
  • bar plot
  • subplots

License

MIT