TensorFlow
Greetings! I'm Vishnu Vinay, a Computer Science and Engineering graduate holding a B. Tech degree. Currently immersed in the captivating world of Artificial Intelligence, I am on a quest for knowledge while pursuing a graduate certificate in Artificial Intelligence with Machine Learning. My passion lies in sharing insights and discoveries in the fields of AI, Machine Learning, Artificial General Intelligence, and Robotics through engaging blog posts. Proficient in Python, ML libraries, and algorithms, I find joy in developing and deploying ML models, with a focus on leveraging AWS Sagemaker. Join me on this exciting journey of unraveling the mysteries of AI through the lens of coding, exploration, and the ever-evolving landscape of machine learning. Let's embark on this knowledge-sharing adventure together!
An end-to-end open-source platform.
complete solution, from start to finish (end to end), the source code of the platform is freely available (open source).
Tensors:- multi-dimensional array
Based on the concept of computational graphs.
Computational graphs:- a directed graph where nodes -> operations, edges -> data (tensors) flowing between those operations.
Supports eager execution (default mode) and graph execution.
Eager execution:- code is learned immediately after writing it, line by line. Easy debugging and natural control flow.
Graph execution:- after writing the code, build a graph (consisting of a bunch of operations on a bunch of tensors), then learns that graph. Faster execution compared to eager execution.
# installing tensorflow library
pip install tensorflow
# importing tensorflow
import tensorflow as tf
# Data storing in tensorflow
# constants
a = tf.constant(5)
print(a)
b = tf.constant(10)
c = tf.add(a, b)
print(c)
# variables
var1 = tf.Variable(20)
print(var1)
# 2D array
var2 = tf.Variable([[1, 2], [3, 4]])
var3 = tf.Variable([[5, 6], [7, 8]])
print(tf.matmul(var2, var3))