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Tensorflow

Tensorflow should not be overlooked when learning and implementing deep learning models. One of the most important tools, with numerous built-in libraries and packages, that allows you to build models more quickly and efficiently.
TensorFlow
In this blog, we will learn about a powerful library primarily used in problem-solving in Machine Learning called TensorFlow. Let's begin.
Applications of Tensorflow
In this blog post, we’ll see the applications of Tensorflow and how companies are using Tensorflow in real-world systems. We’ll also see a practical demonstration of a classification-based task on the IMDB dataset.
TensorFlow Ecosystem EASY
This article highlight the whole TensorFlow Ecosystem. TensorFlow is an open-source, free library for Machine Learning and Artificial Intelligence.
Author Shiva
0 upvotes
TensorFlow Functions to make Deep Learning Easier
In this blog post, we’ll see how some TensorFlow Functions can make some Deep Learning and ML tasks easier.
Neural Style Transfer with TensorFlow MEDIUM
This blog will discuss the topic of Neural Style Transfer with TensorFlow, along with definition, components, working, formulas and implementation.
TensorBoard EASY
This article will learn about tensorboard with its applications, covering all its basics from its installation to its implementation.
Confusion Matrix with Tensorboard EASY
In this article, we will learn to plot a confusion matrix using a tensorboard. To do, so we will be implementing a small neural network and plotting the results in a confusion matrix.
MobileNet EASY
This article talks about MobileNet and its implementation
Learning Variables in Tensorflow with tf.variable EASY
This article incorporates the variable in TensorFlow in Python.
Finding Gradient in Tensorflow using tf.GradientTape MEDIUM
In this blog, we will discuss the introduction to automatic differentiation and then will discuss about the tf.gradientTape, and what are the various methods in tf.gradientTape.
Introduction to Tensorflow Cloud EASY
This article will discuss Tensorflow and Tensorflow cloud in detail.
Tensorflow Advanced: Tensor Slicing MEDIUM
This article will discuss Tensor Slicing in Tensorflow along with its applications.
Tensorflow Advanced: Sparse and Ragged Tensors EASY
This article will discuss the Sparse and Ragged Tensors in Tensorflow.

KERAS

KERAS is a popular library for working with neural networks and is an exclusive interface for working with Tensorflow. Reliable tool for managing the backend operations of deep learning models.
Saving and Loading Model with Keras MEDIUM
This article will discuss the Saving and Loading Model with Keras.
Applications of Keras
This blog is mainly oriented towards the Short introduction and the applications of Keras. Let's get started.
Interesting facts about Keras
In this blog, we will see the theory and implementation of Keras model. Let’s begin.
LR Schedulers in Keras EASY
This article will teach us about LR Schedulers in Keras, exploring their importance, types, implementation and method of selecting them.
Transfer Learning with Keras EASY
The main aim of this blog is to deliver an in-depth explanation of implementation to transfer learning with keras.
Predicting Sentiments with Keras MEDIUM
In this blog, we will discuss sentiment analysis in Keras by predicting sentiments in the IMDB movie reviews dataset.
Performing Masking and Padding using Keras EASY
This article titled Performing Masking and Padding using Keras will give an idea about what and how Padding and masking work in keras.
Visualizing Vision Models in Keras MEDIUM
This article discusses the methods available for visualizing vision models in Keras in Python.
Building a Sentence Similarity Finder in Keras MEDIUM
This article discusses the complete process of building a sentence similarity finder model in Keras.
Building Custom Layers in Keras MEDIUM
This article discusses the complete process of building custom layers in Keras in Python.
Optimizing Models for CPU-based Deployments in Keras HARD
In this blog, we will discuss ONNX for converting the Keras model into ONNX Model for optimizing modes for CPU-based deployments in Keras.

PyTorch

This is a well-known library for machine learning and deep learning applications. Its packages and methods can also be applied to NLP and computer vision models. Supported by Facebook's research lab.
Introduction to PyTorch
In this blog, we will learn a new deep learning framework called PyTorch and its implementation using Python. Let's begin.
PyTorch Tensors
In this blog, we’ll learn and implement how to deal with the tensors using the PyTorch library.
torch.nn Module in PyTorch EASY
This article will take you through the torch.nn module in PyTorch, its uses, and the implementation of various functions and methods present in it.
Transfer Learning using PyTorch MEDIUM
In this blog, we will discuss scenarios in transfer learning and understand transfer learning using Pytorch with the help of an example.
LSTMs and Bi-LSTM in PyTorch MEDIUM
In this article, we will discuss the LSTM and Bi-LSTM along with its implementation. Then we will also discuss the difference between them.
Regression With PyTorch EASY
In this article, we will learn about linear regression and implement it with the help of PyTorch.
PyTorch API for Distributed Training HARD
In this article, you will learn about PyTorch API for Distributed Training, how PyTorch API is helpful, and distributed training example.
Generating Adversarial Examples using PyTorch MEDIUM
This article will take you through all the models and essential facts related to Adversarial Examples of PyTorch.
Dog vs Cat Classifier using Pytorch MEDIUM
In this article, we will discuss the dog vs cat classifier along with its implementation, where the training and validation of data will be done.
How to Migrate from PyTorch to PyTorch Lightning HARD
In this blog, we will discuss How to migrate from PyTorch to PyTorch Lightning, including the pros and cons of Pytorch Lightning.
Exporting models for serving using TorchServe EASY
TorchServe is a PyTorch open-source model serving library. We will examine what are the phases that are needed to export a model for serving using TorchServe.
ML Compilers in PyTorch
This article will teach us about ML Compilers in PyTorch. We will learn about PyTorch, compilers and their various kinds in PyTorch.
Recurrent Neural Networks with PyTorch HARD
This article discusses the basic workings of a recurrent neural network and some of its drawbacks.
Introduction to TorchScript EASY
This article titled introduction to TorchScript contains all the required information and implementation about TorchScript.
Converting PyTorch to TorchScript MEDIUM
In this blog, we will be discussing PyTorch and TorchScript in detail followed by how to convert PyTorch to TorchScript format.
How to Split a Torch Dataset MEDIUM
In this article, we will discuss Split Dataset, its splitting techniques and its handling mechanism.
Resnet in PyTorch MEDIUM
This article will teach about Resnet in PyTorch. We will also discuss the residual block, implementation, and comparison between Resnet and other CNN architectures.
Transformers in PyTorch HARD
In this blog, we will be discussing transformers in PyTorch in detail along with its implementation using the Hugging Face library.
Quantization in Pytorch EASY
In this article, we will discuss quantization, need of quantization and its various PyTorch quantization Methods.
Pruning in PyTorch MEDIUM
This article will teach us about Pruning in PyTorch, neural networks, the need for Pruning, its types and benefits.
Model Optimization in PyTorch MEDIUM
This article discusses the process of optimizing a deep learning model in PyTorch in detail.
Implement Deep Autoencoder in PyTorch MEDIUM
In this blog, we will discuss deep Autoencoder in PyTorch and implement the autoencoder in PyTorch.
Torchaudio in PyTorch MEDIUM
This article will teach us about TorchAudio in PyTorch, exploring how we can visualize data along with its various applications and examples.

Theano

Discover an important and fascinating Python library for mathematical expressions. Widely used for array operations with improved efficiency and optimization, it also includes integrated support from the GPU and NumPy library.
Introduction to Theano MEDIUM
In this article you’ll learn about one of the python libraries called Theano.
Graph Representation using Theano MEDIUM
In this article, we will learn about Graph Representation using Theano. We will learn graph implementation using Theano and various graph functions in Theano.
API and Optimisation in Theano MEDIUM
In this article, we will learn about features of API in Theano, Various Optimizations Functions in Theano, and Various API Functions in Theano.
Working on GPUs with Theano MEDIUM
In this article, we will learn about GPU programming and using GPU with Theano.
What is Lasagne Library?
This blog explains Lasagne Library. In detail, we will discuss the lasagne library, its features, building models on the MNIST dataset using Lasagne, and many more.
Author Aditi
0 upvotes
Theano vs Tensorflow
This blog explains Theano vs. Tensorflow. In detail, we will discuss theano, TensorFlow, and their features and then the comparison between them.
Author Aditi
0 upvotes
What is Blocks Library?
This blog explains Blocks Library. In detail, we will discuss the blocks library, its features, implementation, and plotting models with blocks.
Author Aditi
0 upvotes