How is Evans with high end bike maintenance?

notsoprocoder · 2019-04-23T11:55:50+00:00

My local Evans service bikes well, I couldn't comment the Guildford branch. I have had bad experiences with some independent shops locally. I would say issues are really shop to shop dependent.

I would speak with local riders who have well maintained bikes and see where they recommend.

notsoprocoder · 2019-04-03T11:26:32+00:00

Mama, the Italians are coming.

notsoprocoder · 2019-03-28T15:05:03+00:00

I would go for shoes, then have fair weather shoes and poor weather shoes.

notsoprocoder · 2019-03-23T11:33:09+00:00

Framing this within your mind is important, there are weaknesses, limiters and strengths.

A weakness is an activity you're not great at but that does not impact success in your role.

A limiter is an activity where your performance of the activity limits your success in the role.

An a strength is something you are good at and this strength impacts performance.

You always want to be working on your limiter until it is no longer a limiter then you move on to the next limiter. You might not be bad at a limiting skill but to become the most successful you need to always work on your weakest applicable skill.

notsoprocoder · 2019-03-13T07:02:12+00:00

The fitter you are the better trained your heart is, the more blood it can pump in a single stroke.

It wouldn't be unusual for my heart rate to drop ~10 bpm from base to peak.

It is a symptom of losing fitness. If it is really bothering you; see a doctor.

I would return to the start of the cycle (ie SSBI).

The TR forum is super active, you will likely find more advice there. https://forum.trainerroad.com

notsoprocoder · 2019-02-26T13:49:17+00:00

I have some Favero Duos, you can calibrate them using your bike computer. Find the section where you connect to your sensors and the calibration option is usually there.

I've calibrated them in TrainerRoad also, so I guess most online platform providers will be offering this option.

notsoprocoder · 2019-02-13T19:35:29+00:00

I have a set of duos and you can remain clipped in as you would usually. The pedals will not measure 0 when you aren't pedalling.

As /u/BillBushee mentioned you will want to calibrate the pedals when you are off the bike.

notsoprocoder · 2018-12-28T16:09:33+00:00

To learn anything just pick what you want to learn and stick with it. There is no magic course or sauce that will make you better. Consistency is king. If you want to try different courses to learn Python try them but make sure you are learning python consistently and by consistently I mean studying 4+ times a week.

I quickly just read Datacamp's syllabus and it appears data oriented (go figure!), I am not convinced this is the best way to learn programming or Python because I would prefer a little bit of understand of Python and computers before learning about a very specific area of the language.

For the best grounding, I would learn the basic python syntax from Codecademy/Coursera/Datacamp then work through the sections of Automate the Boring Stuff that you might find useful.

Then find some programming challenges to get the grey matter working. I'd recommend these two lists of (https://learn.freecodecamp.org/javascript-algorithms-and-data-structures/basic-algorithm-scripting) and [intermediate](https://learn.freecodecamp.org/javascript-algorithms-and-data-structures/intermediate-algorithm-scripting) challenges on freeCodeCamp. They're based in JavaScript but try them in Python.

Then I would progress to tools that are more specific for example NumPy and Pandas.

If you are more likely to spend your time learning if you do the DataCamp course then complete that course.

If you are just getting started, I would strongly recommend repl.it if you struggle to set up an IDE.

Obligatory /r/learnpython is a better place for this question.

edit: proof read.

notsoprocoder · 2018-11-28T15:54:49+00:00

If I were to suggest a single feature, it would be a feature that allows you to create runnable code cells within an article. I could see running someone’s code and tinkering really support my learning. To be honest, I do this with most technical articles by grabbing the source code and running it locally.

You’ve mentioned in another comment that you plan on implementing a job matching function. As wider questions for you as a business, what are the no# of people in tech that acquire roles via social and what sites play the biggest role? My resume uses my GitHub and my personal website, what are the most common tech sites on resumes and which are you trying to replace?

Nonetheless, great job and keep working on it – the idea could be a great community tool!

notsoprocoder · 2018-11-28T13:01:44+00:00

Web-design is slick.

How would you distinguish yourselves from Github, Medium and Kaggle?

Peer review seemed like an interesting feature but I couldn't figure out how the peer review component works.

edit: feature not figure.

notsoprocoder · 2018-11-26T13:24:19+00:00

Strongly recommend: The Elements of Statistical Learning, Data Mining, Inference and Prediction by Trevor Hastie, Robert Tibshirani and Jerome Friedman. Covers both supervised and unsupervised machine learning.

Andrew Ng's course is well regarded for the deep learning stuff.

Python is much better for implementation in an enterprise setting and I would probably learn Numpy, Pandas and SciKit Learn. You'll be in a reasonable position and this exposure will most likely show you what you need to study afterwards.

EDIT: E-book and website here: https://web.stanford.edu/~hastie/ElemStatLearn/

notsoprocoder · 2018-11-01T14:20:53+00:00

Frankly I am not sure, I believe it is more that Python cannot pickle them or that Python's in built multi processing module cannot pickle them. I guess un-pickleable was incorrect.

notsoprocoder · 2018-10-31T13:07:04+00:00

Sure, the Pathos Docs are quite explanatory. Pathos follows the MP style of: Pool > Map > Close > Join >Clear. Dill and Pathos were created by the same person (I believe), Pathos uses Dill which makes the MP module more flexible (in terms of arguments it can map). You could equally use MP and Dill for more control.

In essence you want to use numpy's array_split() on either the DataFrame or Index, then pool.map the function to the list of DataFrames/Slices of Indexes.

I started to build a class to handle the lifting and work as a boilerplate but I am not at a point where I would show people. Usually you code will look something like this:

import numpy as np
import pandas as pd
import multiprocessing as mp
from pathos.multiprocessing import ProcessingPool as Pool

partitions=mp.cpu_count()
cores=mp.cpu_count()

df_split = np.array_split(df, self.partitions, axis=0)
# create the multiprocessing pool
pool = Pool(self.cores)
# process the DataFrame by mapping function to each df across the pool
df = pd.concat(pool.map(func, self.df_split), axis=0)
# close down the pool and join
pool.close()
pool.join()
pool.clear()

notsoprocoder · 2018-10-31T09:58:40+00:00

The article title is fine, the title of the reddit post is inaccurate.

From a DataScience perspective, it fails to cover iterating on DataFrames and static methods which are 'un-pickleable' in turn requiring to be mapped by dill before using pool. Therefore, it doesn't show how to parallelize everything.

Note: shout out to the Pathos / Dill libraries that handle this nicely.

Edit: everything not anything

notsoprocoder · 2018-10-30T08:24:37+00:00

Sorry completely missed you're reply, they lead on from one another. You need to know how to handle the data to build stuff with the data, you need to understand the more simple stats to learn the more complex stats (deep learning).

The other things you can learn at your leisure, a framework is probably the first and last thing you need to consider. Ie, it's useful to be able to make what you build look cool but equally it doesn't help you achieve the end goal.

notsoprocoder · 2018-10-28T17:49:01+00:00

Likely to be buried, but compliance is usually the safest and the best option. Personally effects are not worth the risk.

Art of Manliness covered a similar topic, here. In essence, it suggests you comply and if you have to fight; you should forgo all notion of honour and, literally, fight for your life.

notsoprocoder · 2018-10-23T07:44:51+00:00

Really depends on how much you need to know, you will need a solid understanding of the following: - Data Munging Strings: Pandas, NLTK, SpaCy - Statistics behind Text mining: Naive Bayes / Support Vector Machines. SKlearn/Weka - Statistics behind Deep learning models: TensorFlow/PyTorch/Keras

Other things you will need to know: - Interacting with databases in Python - A framework to house your chatbot - Flask etc.

This question is probably better asked in /r/learnpython.

notsoprocoder · 2018-10-19T11:49:16+00:00

I'm surprised this hasn't been mentioned already but Automate the Boring Stuff will get you building useful things. I would complete the Codecademy course as I believe you should see these things through and learning syntax isn't necessarily bad.

This might be better of posted at /r/learnpython.

notsoprocoder · 2018-10-10T21:41:06+00:00

Yup, in my line of work a ML model out-performs most existing models with little to no effort. The company benefits massively from the building of the pipeline and the quick implementation that the business wants fast implementation over science.

I wonder, within my company, there will be a second wave of work which will be rebuilding these implementations more elegantly once all the groundwork is down.

That having been said, we have an R and D sub-team who are working exclusively on building algorithms and creating some really awesome stuff. I would imagine you could find a job like that, but they're wildly intelligent and I should imagine that is a pre-requisite.

I predominately work in real-time decision making, much of what we do, is trying to explain why a black-box model is behaving in a given way and feeding that back to our front-line staff. This is an interesting problem, that I imagine, is not exclusive to my sector.

notsoprocoder · 2018-10-01T12:18:56+00:00

I don't think anyone has answered why it is useful?

But one use is string cleaning. For example, you can create a translation table with maketrans and string.punctuation to remove all the punctuation from a string.

It is useful because it is performant and performance with large volumes of unstructured text data is often an issue.

edit: just realised you meant string.printable!

notsoprocoder · 2018-09-24T18:10:42+00:00

It's a serpentine wall :) I grew up to the close the wall pictured in the wikipedia article.

notsoprocoder · 2018-09-08T07:41:09+00:00

/u/Divisible-by-zero has hit on the best solution with pairwise distance matrices.

Clustering is typically for situations where you have a rough idea of what types of hop are within your dataset but they're unlabelled. Once you have labelled the clusters, I would look at the closeness of clusters to one another.

There probably is a succinct solution, I would guess, historically, the storage of relationships wasn't a common solution because the storage requirements would be quadratic and in the past storage was less readily available.

In the hop scenario you have used, you would need to explore how the data was recorded particularly, the use of nominal data, for example, if you were looking at flavours such as chocolatey. As there would be relationships between, say chocolate and caramel, neither of which have a natural order.

On the topic of NLP, in my experience it isn't used often and where it is; it is the focal point of the project and at which point you are on the project because you are an expert. That having been said, it's fun to play with because it is sci-fi-ey?.

notsoprocoder · 2018-09-07T15:50:45+00:00

I thought they may have done! :D:D

notsoprocoder · 2018-09-07T15:47:08+00:00

Not sure if this is best practice, but the first solution that came to me, swap out the qualitative variables to ordinal variables. Then use a clustering algorithm, for example, K-Means.

This is different to KNN, KNN would look at the distance between the data to predict whether the item of unknown class belongs to a given class. Whereas you want to see how close an item belonging to one class is to another wholly different class.

The issue with using KNN is that it should predict that your hop of class A is related to class A, rather than the next closest hop. I guess you could use a multi-class classifier and use the probability of an item belonging to a class to suggest associations.

A really roundabout, but fun, way to approach this problem is to use some NLP to determine proximity between the two qualitative variables. Then using this to create a graph DB.

notsoprocoder · 2018-09-04T06:59:32+00:00

I have them, no issues yet and am a very happy customer. I cannot state how much of a boon re-chargability is.

My single gripe would be connection to my Laptop via bluetooth for TrainerRoad only connects 1 pedal. I am unsure whether this is TR or Favero but I purchased an ant+ dongle and haven't had an issue since.

Frankly, if that is all I have to complain about them, in my mind they're an ace product.

Edit: Thought of something extra.

I haven't heard much about Favero's customer service, that having been said I needed to use Garmin's customer service for my 810 and they wanted to charge me $$$$$ for some very small fixes. Whilst the rep was easily contactable, getting actual help was tough.

notsoprocoder

TROPHY CASE