TensorFlow

No matching distribution found for TensorFlow using pip [SOLVED]

In this article, we have presented the reason behind the error "No matching distribution found for TensorFlow using pip" along with 3 approaches to fix it.

TensorFlow

Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX AVX2 AVX512 VNNI FMA [Solved]

In this article, we have understood the reason behind the warning "TensorFlow binary was not compiled to use: AVX AVX2 AVX512 VNNI FMA" and presented 3 fixes using which the warning will not come.

TensorFlow

tf.reshape(): Reshape tensors in TensorFlow

In this article, we have explored the idea of Reshaping tensors in TensorFlow with tf.reshape() and which models like GoogleNet use it.

TensorFlow

Max Pool and Avg Pool in TensorFlow

In this article, we have explored Max Pool and Avg Pool in TensorFlow in depth with Python code using the MaxPool and AvgPool ops in TensorFlow.

TensorFlow

Conv2D operation in TensorFlow

In this article, we have explained Conv2D operation in TensorFlow along with API definition and Python implementation.

TensorFlow

Depthwise Convolution op in TensorFlow (tf.nn.depthwise_conv2d)

This article will discuss about the Depthwise Convolution operation and how it is implemented using the TensorFlow framework (tf.nn.depthwise_conv2d).

TensorFlow

Graphs in TensorFlow (tf.Graph)

In this article, we have explored the idea of Graphs in TensorFlow in depth along with details of how to convert function (tf.function) to graph (tf.Graph).

TensorFlow

Visualizing Neural Network Models in TensorFlow

In this article, we have explored the approach to visualize Neural Network Models in TensorFlow. We have explored how to use TensorBoard.

TensorFlow

New features in TensorFlow v2.8

TensorFlow 2.8 has been finally released. Let us take a look at some of the new features and improvements being rolled out in this version. This new version comes with lots of additions, bug fixes and changes.

Machine Learning (ML)

One hot encoding in TensorFlow (tf.one_hot)

This article discusses about one of the commonly used data pre-processing techniques in Feature Engineering that is One Hot Encoding and its use in TensorFlow.

TensorFlow

Initializing Tensors in TensorFlow

In this article, we have explored the idea of Tensors in TensorFlow, different types of tensor and how to initialize and use them.

TensorFlow

Dropout operation in TensorFlow (tf.nn.dropout)

This article discusses about a special kind of layer called the Dropout layer in TensorFlow (tf.nn.dropout) which is used in Deep Neural Networks as a measure for preventing or correcting the problem of over-fitting.

Machine Learning (ML)

MatMul in TensorFlow

In this article, we have explored MatMul operation in TensorFlow (tf.linalg.matmul()) and have presented a sample TensorFlow Python code performing MatMul (Matrix Multiplication).

Machine Learning (ML)

Dense Layer in Tensorflow

We have explained Dense Layer in Tensorflow with code examples and the use of Dense Layer in Neural Networks.

Machine Learning (ML)

Recurrent Neural Network (RNN) questions [with answers]

Practice multiple choice questions on Recurrent Neural Network (RNN) with answers. It is an important Machine Learning model and is a significant alternative to Convolution Neural Network (CNN).

Machine Learning (ML)

Convolution Layer questions [with answers]

Practice multiple choice questions on Convolutional Layers with answers. This is the most important layer in a Machine Learning model in terms of both functionality and computation.

Machine Learning (ML)

Questions on Fully Connected (FC) Layer

Practice multiple choice questions on Fully Connected Layers with answers. These are the most important layer in a Machine Learning model in terms of both functionality and computation.

TensorFlow

Advanced Interview Questions on TensorFlow

We have presented advanced interview questions on TensorFlow with multiple options to choose from. Select an answer to find out if you got it right and get explanation for the answer.

TensorFlow

Questions on TensorFlow (with Answers)

We have present the most insightful and MUST attempt questions on TensorFlow with multiple options to choose from. Select an answer to find out if you got it right and get explanation for the answer.

Machine Learning (ML)

Understand Autoencoders by implementing in TensorFlow

Autoencoders are a type of unsupervised neural networks and has two components: encoder and decoder. We have provided the intuitive explanation of the working of autoencoder along with a step by step TensorFlow implementation.

Machine Learning (ML)

Tensorflow.js: Machine Learning through JavaScript

Tensorflow.js is an open-source library with which we can implement machine learning in the browser with the help of JavaScript. It is powered by WebGL and provides a high-level layers API for defining models, and a low-level API for linear algebra and automatic differentiation.

Machine Learning (ML)

Implementing CNN in Python with Tensorflow for MNIST digit recognition

In this article, we will develop and train a convolutional neural network (CNN) in Python using TensorFlow for digit recognifition with MNIST as our dataset. We will give an overview of the MNIST dataset and the model architecture we will work on before diving into the code.

Machine Learning (ML)

Logistic Regression in Python with TensorFlow

We will walk you though the difference between Linear and Logistic Regression and then, take a deep look into implementing Logistic Regression in Python using TensorFlow. We used the Iris dataset and have trained and plotted the loss function and the training and test accuracy across epochs

Machine Learning (ML)

Training, saving and loading Artificial Neural Networks in Keras

We demonstrate how to code a Artificial neural network model and train and save it in JSON or H5 format which can be loaded later for any inference task. We use Keras/ TensorFlow to demonstrate this transfer learning and used Pima Indian Diabetes dataset in CSV format

Machine Learning (ML)

Linear Regression in Python with TensorFlow

In this guide, we will implement Linear Regression in Python with TensorFlow. Linear Regression is a simple yet effective prediction that models any data to predict an output based on the assumption that it is modeled by a linear relationship.