‘Machine Learning’ Archives
You don’t need a PhD or even a masters to do machine learning. On taking calculated risks and especially calculated exits from one’s comfort zone. Some notes on soul searching and how to choose a career that is also a passion. Reading list.
Jesse Steinweg-Woods is soon-to-be a Senior Data Scientist at tronc, working on recommender systems for articles and understanding customer behavior. Previously, he worked at Argo Group Insurance on new pricing models that took advantage of machine learning techniques. He received his PhD in Atmospheric Science from Texas A&M University, and his [...]
To do Machine Learning in SKlearn, as a first step we need to import following import pandas as pd import numpy as np Step 1. We read the file in Panadas Dataframe by pd.read_csv. In jupyter Note book we defined dataframe as df=pd.read_csv('C:\Data\glass.csv') In order to select features and target for machine learning we will use [...]
In my recent seach on building dummy variables for a loan dataset which I downloaded from kaggle I came across this tutorial on Data preprocessing and feature exploration - step critical building machine learning models models. Though there are still more information I am searching on creating dummy variable, however I like the way presenter [...]
Scikit learn comes with some toy datasets such as iris. We can load these with from sklearn import neighbors, datasets iris = datasets.load_iris() print(iris) However if we try to load any other external, for example I downloaded the wines data from we have to We have to import pandas into SKlearn and then use the following [...]
I found this presentation of Random Forest quite well explained and learned the parameters tuning of optimizing the model as well as Reducing dimensions. That is fairly simple example but helpful in directing us to more advancxed features. Enjoy..
An excellent present on some advanced features of Scikit Learn. This video explore an d present the example on Handwritten digit classification using SVM , Find best best parameters using grid search. This Video also explored doing machine learning on computer network. Lastly a great exaple on Text Data. I selected this video based clarity, easy [...]
Excellent presentation on how to perform predictive analytics on text data. It was presented in Pycon 2016. In this video an example on how to identify spam using Naive Base and regression analysis are used. Very clear presentation by Kevin Markham, Enjoy...Although numeric data is easy to work with in Python, most knowledge created by humans is [...]
An interesting article published in Huffington post by Arshya Vahabzadeh, M.D. Harvard Trained Subspecialist Psychiatrist. Director & Researcher, Brain Power. Academic Faculty, Massachusetts General Hospital. Chair, Council on Communications, American Psychiatric Association. Machine learning already being utilised in healthcare and have [...]
Our client is a well-established leader in online sports gaming with a Technical Centre of Excellence at Yonge and Sheppard. They need an Machine Learning Algorithm Developer. You must be available to spend 1-2 months in Curacao (in the Caribbean) to receive extensive training about sports gaming domain. Of course all your expenses will be paid [...]