Monthly Archives: December 2016

Mental Math Tricks

Will share that soon

Let me love you – One of my favorite DJ mix

Difference between AI, Machine Learning, NLP and Deep Learning

Different terms for:

https://www.quora.com/What-is-the-difference-between-AI-Machine-Learning-NLP-and-Deep-Learning/answer/Dmitriy-Genzel?ref=fb_page

 

Difference between AI, Machine Learning, NLP and Deep Learning

Different terms for:

https://www.quora.com/What-is-the-difference-between-AI-Machine-Learning-NLP-and-Deep-Learning/answer/Dmitriy-Genzel?ref=fb_page

 

Difference between AI, Machine Learning, NLP and Deep Learning

Different terms for:

https://www.quora.com/What-is-the-difference-between-AI-Machine-Learning-NLP-and-Deep-Learning/answer/Dmitriy-Genzel?ref=fb_page

 

Difference between AI, Machine Learning, NLP and Deep Learning

Different terms for:

https://www.quora.com/What-is-the-difference-between-AI-Machine-Learning-NLP-and-Deep-Learning/answer/Dmitriy-Genzel?ref=fb_page

 

Artificial Intelligence will lead the future

Google and the Self-Driving Car

Data Science Track

1. Watch all the videos in youtube regarding data science including algorithms.
2. For data mining complete a series example Rushdi Shams with WEKA
3. For basic theory:
Watch and complete UDACITY, Andrew NG  machine  learning course step by step.
Udacity course I have found much interesting than Andrew NG but I will finish both In Sha Allah
4. There is a UDEMY paid course hands on data science with python
5. For python learn from codeacademy
UBUNTU is good rather windows for python
6. Subeen vaia’s book is also good for python

To be continued

Plagiarism Checker

https://www.grammarly.com/plagiarism-checker

Top 5 popular data science algorithms

Top 5 popular data science algorithms:

Decision Tree
Random Fores
Association Rule Mining
Linear Regression
K-means Clustering

Data science is nothing but extracting and actionable knowledge from data:

Data Scienctist must know data architecture , machine learning, data analytics.

Machine Learning Algorithms(sample)

Continuos:
Unsupervised Supervised
Clustering Regression
Kmeans Linear
SVD Polynomial
PCA Decision Trees
Radom Forests

Categorical:
Association Analysis Classification
Apriori KNN
FP Growth Trees
Hidden Markov Model Logistic Regression
Naive Bayes
Bayes

Supervised Learning: The categories of the data is already known
Unsupervised Learning: The learning process attempts to find appropriate category for the data.

Life Motivation

Look for Love

Love Language:

Motivational Researcher

https://www.acm.org/articles/people-of-acm/2016/fabrizio-sebastiani

Thesis Formatting

 

How AI will lead the future ?

AI Education – Introduction to AI

Posted by Facebook Engineering on Montag, 28. November 2016

 

Artificial intelligence, revealed


My experience with Jarvis has been a little different.

Posted by Priscilla Chan on Dienstag, 20. Dezember 2016