Videos uploaded by user “Laymen's Guide to Machine Learning”
Basics of Python Pandas Indexing with .loc and .iloc:
Video will describe the basics of Python Pandas Indexing using the .loc and .iloc method and the differences between the two
Python Pandas Groupby: Aggregate and Transform
The tutorial explains the pandas group by function with aggregate and transform
Python Pandas Filter Methods
This Video details out the various methods for filtering data
Rpart Decision Tree Tuning
The video details the method of pruning tree using Complexity parameter and other parameters in R. Also it explains the code and method to get the observation in each node in decision tree. node observation set : https://stackoverflow.com/questions/23924051/find-the-data-elements-in-a-data-frame-that-pass-the-rule-for-a-node-in-a-tree-m?rq=1
Python dates and Datetime Module
Suppose you have a date in the string format. How do you convert it into python datetime object and extract features like Year, month and date from it. This is a complete tutorial on the python datetime module and how to work with it.
Difference and Use of Lambda, Apply, Map and Apply Map
The tutorial describes usage and differences among Apply, Apply map and Map.
Random Forest Algorithm: Variable Importance process, sampsize and strata (Part 2)
The video explains the Variable importance algorithm in Random forest and sampsize and strata argument for imbalanced data sets
Python Indexing,  iloc and loc basics (updated version with enhanced audio)
The tutorial describes the basics of python pandas indexing and basics of iloc and loc method. This video is updated version of my video where the audio volume is low
Sql Analytical Function In Pandas: Partition BY, Row Over, Lead and Lag, Top N Rows
This Tutorial explains the SQL like analytical function in Pandas like ranking rows with in a group Partition by row over(), lead and lag function etc.
Concept of Logistic Regression and Use Logit Function
In this video we go over the basics of logistic regression: what is is, when to use it, and why we need it. it also explains how we derive probabilities and use of logit link function. In this video we go over the basics of logistic regression: what is is, when to use it, and why we need it. The intended audience are those who have a little bit understanding of liner regression
Perfect Multi Collinearity in Regression
The tutorial explains the perfect multicollinearity in regression, causes and detection in R
Random Forest Algorithm:  Conceptual Explanation (PART 1)
The tutorial explains the concepts and internal working behind random forest and goes deep into the concepts like out of bag (OOB) sample, boostrap sampling methodology and OOB scoring methodology.
What is Data Science and Machine Learning: The Approach
The video gives a brief introduction of the data science process and pipeline
Model Ensembling techniques
The video tutorial details the three strategies of ensemble modelling 1- one algorithm and different samples like boosting and begging 2- one algorithm and different configuration 3- Many algorithm with chaining