machine learning

MLND Project: Model Evaluation & Validation

10/02/2017 By debkr

3e Project: Model evaluation & validation

Project details

DESCRIPTION:

use Boston house price dataset to PREDICT selling price of a new/unseen home

PROCESS:

EXPLORE data > obtain important FEATURES & DESCRIPTIVE statistics abt data
Properly SPLIT dataset into TRAINING & TEST datasets
DETERMINE suitable PERFORMANCE METRIC for evaluating the problem
ANALYSE performance graphs for learning algorithm over varying TRAINING SET SIZES & with varying number of PARAMETERS
CHOOSE OPTIMAL MODEL that best generalises unseen data
TEST chosen optimal model on a NEW SAMPLE & COMPARE PREDICTED selling price to ACTUAL statistics

Machine Learning Engineering

19/07/2016 By debkr

Dipping a toe in the Udacity pool:
I received an email from the UK/Europe Business Growth Manager of Udacity, looking for people with knowledge of/experiencein Machine Learning to lead and/or support face-to-face training sessions in Machine Learning in London. The email included the link to Udacity’s Nano Degree in Machine Learning.

While I’m not yet skilled or experienced enough at this time to lead a session, I felt really excited that I might have an opportunity to be a session supporter and assistant. That would be cool as I’d be exploring and networking in such an important growth area in tech skills, as well as supporting the growth of MOOCs here in London, which is something I feel really passionately about. [Read more…] about Machine Learning Engineering

Mathematics Mondays (revising some basics)

18/07/2016 By debkr

Here’s a quick revision and recap on some basic maths and linear algebra needed when studying Machine Learning. This will covers basics of calculus and linear algebra. A future post will revise some basic statistics, then I’ll go on todo some quick example calculations of standard deviations, derivatives and matrix determinants.

1. Linear Algebra – matrix multiplication:
Matrices can basically be though of as arrays of numbers, which might be a simple array (equating to a list in Python) which can be expressed as a simple one-row or one-column matrix:

, or they might be more complex matrices with multiple rows or columns: [Read more…] about Mathematics Mondays (revising some basics)

Mathematics Monday: Simple linear regression (revision)

13/06/2016 By debkr

Mathematical compass:
Someone recently suggested I make mathematics my compass (while I was busy diving down rabbit holes reading up on twistors and the like). Maybe they’re correct. I realised that if I was going to do that, I’d need to brush up on my map-reading skills first!

I’ve been so busy engrossed in learning Python I’ve sorely neglected the other streams of the training syllabus I set myself back in late February (is it really that long ago?). So I decided I need to dedicate at least one day a week to bringing my maths back up to speed.

I’m having to start almost back at square one. (Demoralising.) Calculus is a tad rusty to say the least: serious revision required. Did I really quit accountancy for this? Appears to be madness. Surely there’s some hidden logic in there somewhere, it just seems pretty elusive right now. Well, onwards and upwards anyway… [Read more…] about Mathematics Monday: Simple linear regression (revision)

Ed Tech PTP: Summary Syllabus

03/05/2016 By debkr

My newly-established EdTech Personalised Training Plan includes the following streams:

1. Information Theory Stream
2. Learning/Development Stream: how humans learn vs. how machines learn + developing machines to augment human learning
3. Collaborative Learning Stream
4. Innovation Stream
5. Agile Methodologies Stream
6. Educational Technology Stream: to review the technological and presentational innovations shaping education and L&D

Refer my earlier post “Learning About Learning” for some background on this new/additional PTP.

Learning About Learning

03/05/2016 By debkr

As I’ve been going along in this mission of discovery that is my mid-life career-change search, I’ve come to realise just how important Learning & Development really is to me. It’s become a key area for me to look further into – especially in response to my wholly-positive experiences of MOOC’s so far and in relation to my budding interest in all things programming- and technology-led.

I’ve been thinking more and more about the ideas Accelerated Learning and Augmented Learning (specifically in relation to an ongoing developmental Programming Project). In brief, this is about how machine learning and artificial intelligence can be used to help and empower humans, rather than just be there to make rich people more money and put more people out of jobs and into long-term unemployment or underemployment. [Read more…] about Learning About Learning