Machine Learning with TensorFlow Book: различия между версиями
FireWolf (обсуждение | вклад) |
FireWolf (обсуждение | вклад) |
||
Строка 52: | Строка 52: | ||
tf.mod(x, y)—Takes the element-wise remainder from division | tf.mod(x, y)—Takes the element-wise remainder from division | ||
-> 2.4 | -> 2.4. Executing operators with sessions | ||
[[Категория:Работа]] | [[Категория:Работа]] |
Версия 19:36, 25 февраля 2018
Machine Learning with TensorFlow Book by Nishant Shukla
https://github.com/BinRoot/TensorFlow-Book/
Chapter 1
1.4.1 Supervised learning
Descrete with few values - Classifier
Many values and the values have natural order - Regressor
1.4.2. Unsupervised learning
Clustering is the process of splitting the data into individual buckets of similar items.
Dimensionality reduction is about manipulating the data to view it under a much simpler perspective.
1.4.3 Reinforcement learning
Reinforcement learning trains on information gathered by observing how the environment reacts to actions.
2 Tensorflow opertators
tf.constant
tf.zeros
tf.ones
tf.negative
tf.add(x, y)—Adds two tensors of the same type, x + y
tf.subtract(x, y)—Subtracts tensors of the same type, x – y
tf.multiply(x, y)—Multiplies two tensors element-wise
tf.pow(x, y)—Takes the element-wise x to the power of y
tf.exp(x)—Equivalent to pow(e, x), where e is Euler’s number (2.718 ...)
tf.sqrt(x)—Equivalent to pow(x, 0.5)
tf.div(x, y)—Takes the element-wise division of x and y
tf.truediv(x, y)—Same as tf.div, except casts the arguments as a float
tf.floordiv(x, y)—Same as truediv, except rounds down the final answer into an integer
tf.mod(x, y)—Takes the element-wise remainder from division
-> 2.4. Executing operators with sessions