Achievements « Doing It Wrong

Achievements

2/34

Recent Achievements

Stay Away for Seven Days
Give up soda for a week

1/15/2013

STR

LOL 1 PLATE!!! Squat 135 lbs 5×5	It’s Like Standing Squat 1 x Bodyweight 5×5
Squat Lower! Squat 1.5 x Bodyweight 5×5	EXPLODING KNEES Squat 2 x Bodyweight 5×5
Bro-prentice Bodyweight Bench Press 5×5	Prince Bro 1.5 x Bodyweight Bench Press 5×5
Keeping Form 1.5 x Bodyweight Deadlift 1×5	Working Man 2 x Bodyweight Deadlift 1×5
King of the Bros 2 x Bodyweight Bench Press 5×5	Functional Strength Complete Bro-Prentice, Squat Lower!, and Working Man
Fatass! Complete 1 chin-up/pull-up	Getting there… Complete 5 chin-up/pull-ups
Chimp Chump Complete 10 chin-ups/pull-ups	Monkey Man Complete 20+ chin-ups/pull-ups
Starting Strong Complete 3 months of a set program	Commitment Complete 6 months of a set program

CON

No Soda September Give up soda for a month Started: 8/1/2018	Sugar Free Since ’93 Give up soda for a year Started: 8/1/2018
Starter Diet Give up fast food for a month Started: 8/5/2018	Health Nut Give up fast food for a year Started: 8/5/2018
Journey of 1000 Miles Walk 10000 steps a day for a week	Going For A Stroll Walk 10000 steps a day for a month
The Long Walk Walk 10000 steps a day for a six months	Christopher Walken Walk 10000 steps a day for a year

DEX

Running Man
Run a mile in 7 minutes

Speedy Gonzalez
Run a mile in 6 minutes

INT

HAL 8999 100 days of Machine Learning	Neuromancer 1 year of Machine Learning
Mr Roboto CISSP Certification

WIS

Grasshopper Meditate 30 minutes every day for 7 consecutive days	Padawan Meditate 30 minutes every day for 30 consecutive days
Jedi Master Meditate 30 minutes every day for 365 consecutive days	Third Gem’s The Charm Attend group meditation and dharma talk

CHA

Nablopomo Post in my blog every day for 30 days	Nablopo Redux Post in my blog every day for 60 days
Shut Up Already Post in my blog every day for a year

Recent Posts

Cheating Irises by James Martini

HAL8999 7/100 I was sick yesterday but did spend some time looking over some “cheat sheets” that people had put together for various machine learning topics. Some were good, some were just stupid (I’m looking at you Machine Learning in Emoji). Also went through a very simply classifier based on the iris data set.

from sklearn import neighbors, datasets, preprocessing
from sklearn.model_selection import train_test_split
from sklearn.metrics import accuracy_score

# load the data into training and test sets
iris = datasets.load_iris()
X, y = iris.data[:, :2], iris.target
X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=13)

# scale the data
scaler = preprocessing.StandardScaler()
scaler.fit(X_train)
X_train = scaler.transform(X_train)
X_test = scaler.transform(X_test)

# train a k-nearest neighbors model
knn = neighbors.KNeighborsClassifier(n_neighbors = 5)
knn.fit(X_train, y_train)

# Test the model
y_pred = knn.predict(X_test)
print(accuracy_score(y_test, y_pred))

from sklearn import neighbors, datasets, preprocessing

from sklearn.model_selection import train_test_split

from sklearn.metrics import accuracy_score

# load the data into training and test sets

iris = datasets.load_iris()

X, y = iris.data[:, :2], iris.target

X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=13)

# scale the data

scaler = preprocessing.StandardScaler()

scaler.fit(X_train)

X_train = scaler.transform(X_train)

X_test = scaler.transform(X_test)

# train a k-nearest neighbors model

knn = neighbors.KNeighborsClassifier(n_neighbors = 5)

knn.fit(X_train, y_train)

# Test the model

y_pred = knn.predict(X_test)

print(accuracy_score(y_test, y_pred))

[…]

Transformers, more than mee… by James Martini
HAL8999 6/100 Watched the “Learn how to Learn” Google talk on youtube Updated the jupyter notebooks for handson-ml from github and read through the Ch2 notebook to address the CategoricalEncoder issue from yesterday Looked at a basic transformer Part of building a data pipeline is likely to include the creation of custom transformer classes to[…]
from handson-ml import BrokeAsFuck by James Martini
HAL8999 – 5/100 Today while going back through the Hands On Machine Learning book Ch2 I learned that the CategoricalEncoder referenced in the section on handling categorical attributes still isn’t in scikit-learn. I checked the reqirements.txt which shows scikit-learn=0.19.1. Checking my virtualenv, I should be good.

$ grep scikit-learn handson-ml/requirements.txt scikit-learn==0.19.1 $ pip freeze |grep scikit-learn scikit-learn==0.19.2

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$ grep scikit-learn handson-ml/requirements.txt
scikit-learn==0.19.1
$ pip freeze |grep scikit-learn
scikit-learn==0.19.2

Turns out that the CategoricalEncoder isn’t going to[…]
Long days, no blog post by James Martini
HAL8999 – [3,4]/100 Chapter 2 of Hands on ML continues Creation of test sets Stratified sampling sklearn’s StratifiedShuffleSplit Visualizing data with matplotlib Coorelation coefficients Getting a good train-test split Since you can’t train a model and just expect it to work well right out of the box it’s standard practice to split off about 20%[…]