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Notes for Artificial Neural Networks!
Lesson 1: He defines the terminologies as weights denoted by w, bias denoted by b, activation function denoted by g(.), neuron preactivation(I/P) denoted by x, neuron activation(O/P) denoted by h(x). Everything exept b is a vector. He starts a d...…
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Notes for Intro to Data Analysis!
Lesson 1: Data Analysis Process Question Wrangle Acquiring Data Cleaning Data Explore Draw conclusions Communicate The process is iterative and need to go back and forth....…
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Notes for ML!
Lesson 1: ML is algorithms for inferring unknowns from knowns. eg. Filtering out spam, Detect Handwriting, Face Detection, Speech Recognition, Netflix ranking, Navigation, Climate Modelling Classes of ML Supervised vs unsupervised Learn...…
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Notes for Segmentation and Clustering!
Lesson 1: Process of Segmentation Standardisation where we treat a group as a whole Localisation where we treat them as individuals Grouping or binning It becomes difficult to group as the number of variables increase Clustering is a mathema...…
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Notes for Model Building And Validation!
Lesson 1: Example of model building Toxic and non toxic classification Advertising - collaborative filtering QMV iterative process of analysis Questioning Modeling Validating Must choose a metric cap...…
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Notes for Intro to Inferential Statistics!
Lesson 1: Sample mean = Population Mean Sample Standard Deviation = Population Standard Deviation/sqrt(number of samples) = Standard Error z score indicates how many standard deviation is an element from the mean Distribution of sample means i...…
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Notes for Intro to Statistics!
This is the course offered by Sabestian Thrun.Lesson 1: Using statistics he shows how we are actually less popular than our friends in expectation. This is actually called Friendship paradox. He tells how statistics plays a main role in converti...…
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Notes for Neural Networks!
This is the course offered by Jeffery Hilton.Week 1: He starts with a dicussion about the need for machine learning models and talks about the situations where it is really hard to write programs and form rule based solutions since there is no si...…
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Notes for Classification Model!
This is first in the series of notes that I plan to put online which I take during my online courses. This one specifically is from the Udacity Course Classification Models.The course start with a discussion around a problem where we need to predi...…
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Welcome to my blog!
First of all, thanks for visiting my blog.I think of this blog as my scratch book. A place where I can write about my experiences in personal and professional life. Remember the days we used to write diaries in the childhood as Dear Diary, Today...…
