Machine Learning will be embedded everywhere soon.
The size of data available to the world is growing exponentially. No matter what industry or field you are working on, the ability to analyze data is becoming more valuable.
STEPHACKING is designed for people who want to learn about data science, but don’t know where to start.
You can find tutorials and demo on various data science topics here.
All topics are broken into easy steps.
We want you to be able to start your data projects even if you have no mathematical or programming background.
In STEPHACKING, we will keep everything simple and quick.
You will find examples on data analysis using Python or R or VBA. We will break down every step for you so that you can follow easily. Moreover, this site is completely free of charge.
Our goal is to turn topics related to artificial intelligent and machine learning into bite-sized step by step format.
Even if you have ZERO science background, you can also enjoy the fun of machine learning.
Hands-on Machine Learning Projects
Python and R are popular for works related to data manipulation. We will be building projects together step by step; using some of the most popular libraries, such as, Tensorflow, Theano, Pytorch, Keras, Scikit-learn, numpy, matplotlib, pandas.
Learn by Visualizing
Many people learn by visualizing the steps. We will break down the most popular Machine Learning codes for you steps by steps. Just follow the screenshots, and you can enjoy the fun of machine learning.
Machine Learning Topics
Multiple Linear Regression
Support Vector Regression (SVR)
Decision Tree Regression
Random Forest Regression
Principal Component Analysis (PCA)
Linear Discriminant Analysis (LDA)
K-fold Cross Validation
K-Nearest Neighbors (K-NN)
Support Vector Machine (SVM)
Decision Tree Classification
Random Forest Classification
Upper Confidence Bound (UCB)
Natural Language Processing
Artificial Neural Networks
Convolutional Neural Networks
Recurrent Neural Networks