Shadab Hussain techwithshadab

💻

Playing with Data

techwithshadab / byte-sizetuts.md

Created January 11, 2016 15:47 — forked from honkskillet/byte-sizetuts.md

A series of golang tutorials with youtube videos.

byte-size tuts

by alexander white ©

techwithshadab / tensorflow-for-beginners.ipynb

Last active August 2, 2019 19:51

Tensorflow for Beginners.ipynb

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techwithshadab / Tensorflow for Beginners(Importing Packages).py

Last active August 2, 2019 18:13

	import tensorflow as tf
	tf.logging.set_verbosity(tf.logging.ERROR)
	import numpy as np
	import matplotlib.pyplot as plt

techwithshadab / Tensorflow for Beginners(Generate or Import Data Set).py

Created August 2, 2019 18:21

	mar_budget = np.array([60, 80, 100 , 30, 50, 20, 90, 10], dtype=float)
	subs_gained = np.array([160, 200, 240, 100, 140, 80, 220, 60], dtype=float)

	for i,c in enumerate(mar_budget):
	print("{} Market budget = {} new subscribers gained".format(c, subs_gained[i]))

techwithshadab / Tensorflow for Beginners(Visualise Data).py

Created August 2, 2019 18:23

	plt.scatter(mar_budget, subs_gained)
	plt.xlim(0,120)
	plt.ylim(0,260)
	plt.xlabel('Marketing Budget(in thousand of Dollars)')
	plt.ylabel('Subscribers Gained(in thousand)')
	plt.show()

techwithshadab / Tensorflow for Beginners(Split Data).py

Last active August 2, 2019 18:27

	from sklearn.model_selection import train_test_split
	X_train, X_test, y_train, y_test = train_test_split(mar_budget,subs_gained,random_state=42,
	train_size=0.8, test_size=0.2)

techwithshadab / Tensorflow for Beginners(Build a Layer).py

Created August 2, 2019 18:26

layer_0 = tf.keras.layers.Dense(units=1, input_shape=[1])

techwithshadab / Tensorflow for Beginners(Add Layer to Model).py

Created August 2, 2019 18:29

model = tf.keras.Sequential([layer_0])

techwithshadab / Tensorflow for Beginners(Alternate way to add layer to model).py

Created August 2, 2019 18:31

	model = tf.keras.Sequential([
	tf.keras.layers.Dense(units=1, input_shape=[1])
	])

techwithshadab / Tensorflow for Beginners(Compile Model).py

Created August 2, 2019 18:32

	model.compile(loss='mean_squared_error',
	optimizer=tf.keras.optimizers.Adam(0.1))