Understanding Logistics regression

The basis

  • Logistics or Logit regression.
  • It’s a regression model where the dependent variable (DV) is categorical.
  • Outcome follows a Bernoulli distribution.
  • Success = 1 , failure = 0.
  • Natural logarithm of odds ratio ln (p/1-p)… logit(p).
  • Inverse log curve gives a nice “s” curve to work with.
  • Equate logarithm of odds ratio with regression line equation.
  • Solve for probability p

Example

Continue learning the basis !

 

Serverless

Serverless is a buzzword

It points to the future of software development in a post cloud world.

The idea of “Serverless” is NOT about removing the servers completely (or you couldn’t use the internet at all), but essentially paying for services that mean that someone else manages the servers for you thereby reducing maintenance load.

It’s all about reducing the obscurity of cost.

Spend control is a necesary evil that enable the organizations to understand where they are allocating their resources. The allocation of the limited resources at the best place of the organization will enable itself to be more competitive.

Total cost of Ownership (TCO) enables to understand the end to end amount of resources that an visible element consumes at its whole lifecycle. When calculating the TCO, there are always assumptions required as not all costs are direct costs that clearly you can assign to a single asset.

Here is where serverless shows up.

The reduction in obscurity of cost through serverless will change the way we develop, build, refactor, invest, monitor, operate, organise & commercialise almost everything.

The idea is to move to a scenario where you are performing the billing per function, where you are investing as much as possible on visible value for your organization, reducing the OPEX as much as possible, and having understanding about where your resources are allocated.

Simon Wardley did a map that illustrates the case:

Source: https://serverless.zone/serverless-is-just-a-name-we-could-have-called-it-jeff-1958dd4c63d7

Serverless Framework

It is a free and open-source web framework written using Node.js. Serverless is the first framework that was originally developed for building applications exclusively on AWS Lambda, a serverless computing platform provided by Amazon as a part of the AWS.

From the framework, it birh Serverless, that is a toolkit for deploying and operating serverless architectures. Focus on your application, not your infrastructure.

 

 

 

Alexa,

The event,

This Christmas I went to a friend’s home, they had Alexa at home. At one point I was curious about how it worked and what type of things you can ask Alexa.

Play music, ask about weather, add products to the shopping cart, define an alarm to get up…

What stunned me the most…

While so many companies are calling customers by phone or knocking the doors of millions of homes, paying salaries to all these people doing commercial actions; suddenly Amazon makes some of these customers to pay 175$ (I think right now is around 110$) to have a commercial guy at home. To me this is genius.

Idea for future

Alexa is in reality stablishes a basic interrelationship, you make direct questions and the robot replies them, having limited the type of interaction you can have.

Imagine that you can acquire a service where Alexa turns to “John, the basketball supporter of the New York Knicks”, and while you are watching a game in the TV, you can comment with John how the game is going on, ask John what is the best score game of that young player in the University, etc…

How many people that have nobody to talk would benefit from this?

How many roles can be created to increase the interaction with specific human behaviors that are looking someone to talk to?

 

Guru99, python and more

There are so many tutorials about almost everything, this time I found this one: https://www.guru99.com

  • Guru99 Vision: Fun & Free Education for ALL
  • Guru99 Mission: To bring all feasible courses , online.

Python was the one who took the first look, but I went quickly to other tutorials.

I am inmersed now on a SAP HCM project, so I have read the basis of the SAP Infotype organization and other relevant stuff that the consultants are mentioning every single day.

Read tutorials is hard, but these ones are in real “plain english” so you quickly understand the topics. They are focused on people without knowledge of a topic.

Volume Price Confirmation Indicator (VPCI)

I have been looking for volume indicators that help me to identify the right minimum volumes to place long position, but by the moment I was not success.

This time I found this VPCI in tradingview, so let’s see how it works. The notes are very interesting basis of knowledge.

Volume Price Confirmation Indicator (VPCI)

Developed by Buff Dormeier, VPCI won 2007 Charles H Dow award by the MTA. VPCI plots the relationship between price trend and the volume , as either being in a state of confirmation or contradiction.

Fundamentally, the VPCI reveals the proportional imbalances between price trends and volume-adjusted price trends.

  • An uptrend with increasing volume is a market characterized by greed supported by the fuel needed to grow.
  • An uptrend without volume is complacent and reveals greed deprived of the fuel needed to sustain itself.

Investors without the influx of other investors ( volume ) will eventually lose interest and the uptrend should eventually breakdown.

A falling price trend reveals a market driven by fear.

  • A falling price trend without volume reveals apathy, fear without increasing energy. Unlike greed, fear is self-sustaining, and may endure for long time periods without
    increasing fuel or energy. Adding energy to fear can be likened to adding fuel to a fire and is generally bearish until the VPCI reverses. In such cases, weak-minded investor’s, overcome by fear, are becoming irrationally fearful until the selling climax reaches a state of maximum homogeneity. At this point, ownership held by weak investor’s has been purged, producing a type of heat death capitulation. These occurrences may be visualized by the VPCI falling below the lower standard deviation of a Bollinger Band of the VPCI, and then rising above the
    lower band, and forming a ‘V’ bottom.

The code

//
// @author LazyBear
//
// If you use this code in its orignal/modified form, do drop me a note.
//
study(“Volume Price Confirmation Indicator [LazyBear]”, shorttitle=”VPCI_LB”)
shortTerm=input(5)
longTerm=input(20)

src=close
vpc = vwma(src, longTerm) – sma(src, longTerm)
vpr = vwma(src, shortTerm)/sma(src, shortTerm)
vm = sma(volume, shortTerm)/sma(volume, longTerm)

vpci = vpc*vpr*vm
hline(0)
plot(vpci, color=orange, linewidth=2)

DrawMA = input(true, type=bool, title=”Draw MA on VPCI?”)
lengthMA=input(8, “VPCI MA Length”)
s=sma(vpci, lengthMA)
plot(DrawMA?s:na, color=teal)

// Uncomment this line to enable histogram
// plot(DrawMA?(vpci-s):na, color=blue, style=histogram)

DrawBands = input(false, type=bool)
HighlightBreaches = input(true, type=bool)
length=input(20, title=”BB Length”)
mult=input(2.5)
bb_s = vpci
basis = sma(bb_s, length)
dev = (mult * stdev(bb_s, length))
upper = (basis + dev)
lower = (basis – dev)

plot(DrawBands?basis:na, color=gray, style=line)
p1 = plot(DrawBands?upper:na, color=gray)
p2 = plot(DrawBands?lower:na , color=gray)
fill(p1, p2, blue)

b_color = (bb_s > upper) ? red : (bb_s < lower) ? green : na
offs_v = 0.3
breach_pos = (bb_s >= upper) ? (bb_s+offs_v) : (bb_s <= lower ? (bb_s – offs_v) : 0)
Breached=(bb_s >= upper) or (bb_s <= lower)
plot(HighlightBreaches and Breached ? breach_pos : na, style=cross, color=b_color,linewidth=3)

Etherium ecosystem

Simon Wardley says related to maps: practice, practice, practice… so here there is a practice.

The map

Development environment

  • Solidity : is quite mature and the community of developers is increasing, there are so many places where you can learn how to develop in solidity, and the documentation is quite good. There are other languages but not as popular as solidity: Serpent, Mutan, LLL.
  • Certification programs: for developers and for the applications itself. This is a natural step that will happen sometime.
  • B2C Vs B2B: right now the majority of applications are B2C, but I’m sure that in the future some B2B solutions will show up. B2B solutions are more difficult to identify as they are not always advertized publicly, right now the Pioneer CIOs are the main consumers that should be looking at them (settlers and town planners are still not interested on blockchain).
  • Official DApp store : this is something that will have to happen in the future. Right now there are some places publishing lists of available distributed applications, but there are not quality checks and there are not enough volume of users using them and rating them.
  • The API: the ability to interconnect with different environments is key, specially to promote the partnership between DApps that benefit to the end user, and hence enrich the ecosystem.
  • Waste of energy: this is a constrain provoked by Proof of work (POW) method. At some time this should be reviewed. Ethereum is trying to move towards proof of stake in it’s next release Casper.
  • Hyperledger: competition is a healthy fact, and a way to compare the evolution. We cannot compare apples with apples, but there are common components where you can determine some comparisons.
  • Ability to run private transactions : right now this is not possible, you can set the transactions as visible or private for all users, but not for restricted users or roles.
  • Reward for each block: the fact that there is a reward for each completed block makes the community to increase, this is an accelerator to me.

Etherium Vs Hyperledger

They are a different thing that will meet in some future.The main differences can be read here.

  • Etherium      = B2C, POW,                   , built in cryptocurrency…
  • Hyperledger = B2B, No-op and PBFT , no cryptocurrency required…

Remember the basic nomenclature of the maps Any suggestion to improve the map?

Etherium Maturity

This week I noticed 2 things:

Maturity of the ecosystem

I acquired the habit of checking the market capital volume of the 100 top cryptocurrencies. Doing it, I notice how the lifecycle of the currencies are happening. Some new births and some of them that are gone.

I have also checked some ICOs, reading the white papers, trying to understand who is behind them, if they are achieving the calendar communicated, etc.

In the road to reach the mainstream adoption of etherium, I guess there are still so many steps the environment has to take.

Official Etheirum App Store

Right now, there are some places where you can track some number of distributed applications based on Etherium. For instance: dappradar and state of the Dapps.

But they are not an official Store with some quality criteria that ensures some basis is still not there.

Apple, Google, Facebook “app stores”

If you try to publish an application on the Apple Store (that right now to me is the more high quality level one) you will notice that there are so many things that cannot be done with the purpose of protecting the end user.

Google restrictions is also high, but Facebook ones lack of control on some of the data that an application can retrieve from an end user.

What’s happening now?

Right now there are so many gambling games, pyramid schemes, and exchanges places that does not help to mainstream adoption.

Who will be able to drive the situation to the existence of an “official DApp store”?

Etherium is evolving as an ecosystem and the number of early adopters cannot be ignored.

 

Litecoin

Bitcoin and Litecoin  are the global leaders in cryptocurrency, both are powered by similar technologies with the exception that Litecoin is a modified, more efficient version of Bitcoin focused on retail applications. Litecoin, as a result, is both cheaper and faster to transfer than Bitcoin but unfortunately may not be as universally accepted as Bitcoin.

Some advantages with respect Bitcoin:

  1. Faster transaction confirmation time (4x faster than BTC)
  2. Increased storage efficiency due to scrypt usage in LTC proof-of-work algorithm
  3. More coins to reward miners (84mn to be distributed total compared to 21mn BTC).

Litecoin is one of the more popular coins. They stay in the top 5 cryto currencies but during these last weeks the news about LitePay are not helping to the project (March 2018).

Litepay

LitePay was announced to be released around the end of February 2018.

Then it was rescheduled for launching at the beginning of March 2018.

Now the launch has been postponed without defined date.

Litepal

Another payment solution for Bitcoin and Litecoin with a roadmap, that I want to follow up how they deliver.

  • Payment infrastructure ready: 1/May/2018
  • Platform, meet payments: 10/May/2018
  • Developer API release: 17/May/2018
  • Series 1 – Integration: 30/May/2018
  • Series 2 – Integration: 25/June/2018

 

Thinking basketball

In the back side of the book you can read:

Behavioral economics, traffic paradoxes and other metaphors highlight this though-provoking insight into the NBA and your own thinking.

So I bought the book.

Ben Taylor Author Profile: News, Books and Speaking Inquiries

Some remarks to remind

Individual scoring is not replaced, it is redistributed.

Look at the global impact of a player, not just to the score.

Scoring blindness

A tendency to focus on a individual’s scoring while overlooking his other actions that influence the team score.

Individual players are limited in their impact (measured through WOWY (with or without you) method).

Variance, rules of thumb

  1. Low variance is “consistent”
  2. High variance is “inconsistent”
  3. The greater the variance, the larger sampple needed to make accurate conclusions.

Sample size insensitivity

A tendency to consider the given sample as sufficient for reaching a conclusion.

Winning bias

When a team wins, in order to explain why they won, we sift through memories of the positive events in the game. When a team losses, we eximine the negatives. This phenomenom is at the crux of winning bias.

Winning bias: a tendency to overrate how well an individual performed because his team won and underrate how well an individual performed because his team lost.

Winning bias creates a selection filter to find evidence that supports a particular conclusion.

Late game bias

A tendency to incorrectly weigh events as more important the later they occur in the game.

  • Good teams win early.
  • Clutch play matters little.
  • Hero ball and isolation plays are low-efficiency.
  • Good teams and good offenses don’t need to rely on a “closer” while bad clutch teams can be great NBA champions.

All of these beliefs about the importance of crunch-time, for both teams and players, come from late-game bias.

The rings fallacy

The false belief that championship rings in team sports are a relevant determiner of an individual’s performance.

Championship hindsight

The false belief that after a season ends, only the team that won was a “championship” level team.

Portability

How well a player’s skill travels to other, retaining value on successful teams. For instance assistants, passings, rim protection…

Lone star illusion

A tendency to cover-credit one player with the majority of a team’s success when there are no other all-stars on the team.

Heuristics

Our mental scoreboards are constructed from heuristics: a way to seek the solution of a problem through non-rigorous methods, such as by trial and error, empirical rules.

Heuristics is basically intuition, guess.

Our heuristics become crutches for our narratives. Over the years we have developed a tendency to focus on individual scoring at the expense of Global Offense or Global Defense contributions.

Bias

The book reviews different bias that are present in the way the narratives are done, simplifications are set, etc. To me the explanation of these specific bias and the way the narratives are done is the most valuable learning from the book.