Category Archives: Research

Machine Learning Scikit Learn

Machine Learning with Python

 

Natural Language Processing, Text Summarization,

 

 

 

Neural Network: Machine Learning

 

Machine Learning Mastery

The Naive Bayes algorithm is simple and effective and should be one of the first methods you try on a classification problem. In this tutorial you are going to learn about the Naive Bayes algorithm including how it works and how to implement it from scratch in Python. Update: Check out the follow-up on tips for …

 

Machine Learning in MATLAB: KNN

 

Statistics: For Machine Learning: Random Variables : Discrete and Continuous

 

 

Must See:

 

Probability is the measure of how likely an event is to occur out of the number of possible outcomes. This wikiHow will show you how to calculate different types of probabilities. Define your events and outcomes. Probability is the…

Machine Learning is Solving Real Life Problems

 

How to find Research Topic to Concentrate

https://cstheory.stackexchange.com/questions/9954/how-to-find-a-specific-research-topic-to-concentrate-on

Training Set, Validation Set, Test Set

Training Set is a subset of the dataset used to build predictive models.
Validation Set is a subset of the dataset used to assess the performance of model built in the training phase
– It provides a test platform for fine-tuning model’s parameters and selecting the best performing model
– Not all modeling algorithms need a validation set
Test set or unseen examples is a subset of the dataset to assess the likely future performance of a model.
– If a model fits the training set much better than it fits the test set. Overfitting is probably the cause

 

Binary Classification(two class classification)

true|false, 1|0, -1|+1, male|female

Multi-class classification problems can be seen as binary classification problems.

Model Evaluation:

 

https://en.wikipedia.org/wiki/Confusion_matrix

Machine Learning in Easy Way


Deep Learning, Deep Neural Network:

 

Road to Data Scientist and Python Ninja

Here , I will try to share some of the info about data scince mastery step by step and pythonic attitude :p

These links may help:

https://www.quora.com/Which-career-is-more-promising-data-scientist-or-software-developer-1

https://www.inferentialthinking.com/

https://chrisalbon.com/

https://www.facebook.com/groups/pythonbd/permalink/814281808673238/

Data Podcats:
https://dataskeptic.com/

 

Python:

https://www.coursera.org/specializations/python
https://pythonspot.com/en/

 

Job:

https://whoishiring.io

 

Heading Towards My Journey To Data Science Strongly..The sexiest job of 21st century

Chatbot:
https://chatbotslife.com/machine-learning-for-dummies-part-1-dbaca076ec07

Sentiment Analysis, Natural Language Processing:
https://medium.com/udacity/natural-language-processing-and-sentiment-analysis-43111c33c27e

Data Science MOOC (Will do someday)

http://www.kdnuggets.com/2015/09/top-20-data-science-moocs.html

https://lagunita.stanford.edu/courses/Home/Databases/Engineering/about

Data Science: Discrete vs Continuous