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Concepts and Tools
Last updated: Feb 7, 2022

Concepts and Tools

Learn about important deep learning concepts that will help you throughout the learning process, as well as tools that will help you build models and improve algorithms, such as Tensorflow, KERAS, and PyTorch.
Binary Classification
In this blog we have discussed Binary Classification, followed by developing, visualizing the Model.
Author Mandla Dharani
1 upvote
Vectorization
This blog will study vectorization and use it in Machine Learning to write cleaner and optimized code.
Author Chaturvedi
4 upvotes
Residual Analysis MEDIUM
In this blog, we will learn about Residual Analysis. We will further in the blog, learn about residual analysis in Python.
Author Gunjan Batra
1 upvote
Vectorizing Logistic Regression
In this article, we will discuss the vectorized form of logistic regression. Furthermore, we will implement code for the vectorized form of logistic regression.
Author soham Medewar
4 upvotes
Understanding Forward Propagation
This blog thoroughly discusses Forward propagation in ANNs and how it differs from Backpropagation.
Author Arun Nawani
1 upvote
TensorFlow vs. PyTorch vs. Keras
In this blog, we will see three deep learning frameworks: Keras, TensorFlow, and PyTorch and their use cases. Let's begin.
Author Rajkeshav
0 upvotes

Perceptron

One of the fundamental algorithms for working on classification in neural networks. Learn about its implementation, significance, and visualisations.
What is Perceptron? EASY
This blog extensively covers perceptrons and their applications in the real world.
Author Arun Nawani
2 upvotes
Visualizing Decision Boundary (Perceptron)
In this article, we will make a model and visualize the decision boundary in the perceptron learning algorithm.
Author soham Medewar
0 upvotes

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.
Author Rajkeshav
0 upvotes
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.
Author Chaturvedi
0 upvotes
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.
Author Chaturvedi
1 upvote
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.
Author Sagar Mishra
0 upvotes
TensorBoard EASY
This article will learn about tensorboard with its applications, covering all its basics from its installation to its implementation.
Author Mayank Goyal
0 upvotes
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.
Author soham Medewar
0 upvotes
MobileNet EASY
This article talks about MobileNet and its implementation
Author Mohammad Yawar
0 upvotes
Learning Variables in Tensorflow with tf.variable EASY
This article incorporates the variable in TensorFlow in Python.
Author Amit Singh
0 upvotes
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.
Author Vaibhav Agarwal
0 upvotes
Introduction to Tensorflow Cloud EASY
This article will discuss Tensorflow and Tensorflow cloud in detail.
Author Lali Sharma
3 upvotes
Tensorflow Advanced: Tensor Slicing MEDIUM
This article will discuss Tensor Slicing in Tensorflow along with its applications.
Author Shubham Das
0 upvotes
Tensorflow Advanced: Sparse and Ragged Tensors EASY
This article will discuss the Sparse and Ragged Tensors in Tensorflow.
Author Shubham Das
0 upvotes

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.
Author Shubham Das
0 upvotes
Applications of Keras
This blog is mainly oriented towards the Short introduction and the applications of Keras. Let's get started.
Author Rajkeshav
0 upvotes
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.
Author juhipathak
0 upvotes
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.
Author Anjujais
0 upvotes
Predicting Sentiments with Keras MEDIUM
In this blog, we will discuss sentiment analysis in Keras by predicting sentiments in the IMDB movie reviews dataset.
Author Ayush Mishra
0 upvotes
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.
Author Lali Sharma
0 upvotes
Visualizing Vision Models in Keras MEDIUM
This article discusses the methods available for visualizing vision models in Keras in Python.
Author Sohail Ali
1 upvote
Building a Sentence Similarity Finder in Keras MEDIUM
This article discusses the complete process of building a sentence similarity finder model in Keras.
Author Sohail Ali
1 upvote
Building Custom Layers in Keras MEDIUM
This article discusses the complete process of building custom layers in Keras in Python.
Author Sohail Ali
1 upvote
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.
Author Ayush Mishra
0 upvotes

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.
PyTorch Tensors
In this blog, we’ll learn and implement how to deal with the tensors using the PyTorch library.
Author Chaturvedi
0 upvotes
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.
Author Prakriti
0 upvotes
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.
Author Ayush Mishra
0 upvotes
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.
Author lakshayhere
0 upvotes
Regression With PyTorch EASY
In this article, we will learn about linear regression and implement it with the help of PyTorch.
Author Mayank Goyal
0 upvotes
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.
Author Muskan Sharma
0 upvotes
Generating Adversarial Examples using PyTorch MEDIUM
This article will take you through all the models and essential facts related to Adversarial Examples of PyTorch.
Author Lali Sharma
0 upvotes
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.
Author lakshayhere
0 upvotes
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.
Author Aditya Gupta
0 upvotes
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.
Author Vidhi Sareen
0 upvotes
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.
Author juhipathak
0 upvotes
Recurrent Neural Networks with PyTorch HARD
This article discusses the basic workings of a recurrent neural network and some of its drawbacks.
Author Abhinav Anand
0 upvotes
Introduction to TorchScript EASY
This article titled introduction to TorchScript contains all the required information and implementation about TorchScript.
Author Lali Sharma
0 upvotes
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.
Author Akanksha Burnwal
0 upvotes
How to Split a Torch Dataset MEDIUM
In this article, we will discuss Split Dataset, its splitting techniques and its handling mechanism.
Author Jagriti20
0 upvotes
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.
Author Vidhi Sareen
0 upvotes
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.
Author Akanksha Burnwal
0 upvotes
Quantization in Pytorch EASY
In this article, we will discuss quantization, need of quantization and its various PyTorch quantization Methods.
Author Jagriti20
0 upvotes
Pruning in PyTorch MEDIUM
This article will teach us about Pruning in PyTorch, neural networks, the need for Pruning, its types and benefits.
Author juhipathak
0 upvotes
Model Optimization in PyTorch MEDIUM
This article discusses the process of optimizing a deep learning model in PyTorch in detail.
Author Sohail Ali
1 upvote
Implement Deep Autoencoder in PyTorch MEDIUM
In this blog, we will discuss deep Autoencoder in PyTorch and implement the autoencoder in PyTorch.
Author Aditya_2bc4
0 upvotes
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.
Author juhipathak
0 upvotes

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.
Author Muskan Sharma
0 upvotes

Caffe2

Caffe2 is a C++-based library that also supports Python and MATLAB. It is widely used for Deep Learning operations, with a wide range of architectures and maps ranging from neural networks to encoders. Caffe2 is now part of PyTorch, but it is still useful.
Introduction to Caffe2 Framework
This blog explains the details of Caffe2 along with Features of Caffe2, Brewing Models with Caffe2, Ops, Helper Functions, and Caffe2 Integrations with C++.
Author Nilesh Kumar
0 upvotes
PyTorch vs Caffe2
This blog explains the details of PyTorch vs Caffe2 along with a brief about PyTorch and Caffe2, Features of PyTorch, Features of Caffe2, and a comparison between PyTorch vs Caffe2.
Author Nilesh Kumar
0 upvotes

SparkML

SparkML is an abbreviation for Apache Spark's Machine Learning library. It is quicker and includes API for pipelining. In this category, you can learn about its features, pipelining methods in SparkML, and much more.
Introduction To Spark ML MEDIUM
In this article, we will look into Spark ML and we will also see a few examples to understand Spark ML better.
Author Sajid
0 upvotes
PySpark Tutorial MEDIUM
In this blog, we will look at a detailed Pyspark tutorial. This includes the setting up of PySpark along with its various components like APIs, libraries, etc.
Author Avni Gupta
1 upvote
Introduction to Apache Spark GraphX MEDIUM
This article discusses the main features and uses of Apache Spark GraphX and shows how to analyse data using GraphX.
Author AkshatAggarwal
0 upvotes

Miscellaneous

Learn about other Deep Learning and Machine Learning-based libraries and packages, as well as their applications and implementations for creating and solving interesting deep learning models and algorithms.
CuPy v/s NumPy EASY
The blog follows a brief series of concepts starting with features of CuPy and NumPy followed by a comparison of them.
Author Komal
0 upvotes