Sentiment analysis refers to the use of natural language processing, text analysis, computational linguistics, and biometrics to systematically identify, extract, quantify, and study affective states and subjective information. Wikipedia
Sentiment analysis (or opinion mining) is a natural language processing technique used to determine whether data is positive, negative or neutral. Sentiment analysis is often performed on textual data to help businesses monitor brand and product sentiment in customer feedback, and understand customer needs.
In today’s article, we are going to talk about five 5 Unknown Sentiment Analysis Projects On Github To Help You Through Your NLP Projects to enhance your skills in the field of data science and machine learning.
Note: In this article, we are going to talk about some ‘low ball’ but really good open-source Sentiment Analysis projects which you can use in your projects. …
Natural language processing is a subfield of linguistics, computer science, and artificial intelligence concerned with the interactions between computers and human language, in particular how to program computers to process and analyze large amounts of natural language data. Wikipedia
Natural Language Processing explains that in NLP, machines are taught to read and interpret the text as humans do. NLP is recognized as the “enabler of text analysis and speech-recognition applications.” This human capability for interpreting text comes in handy for analyzing large volumes of text data. The technology can accurately extract information and insights contained in the documents as well as categorize and organize the documents themselves.
In today’s article, we are going to talk about five of the NLP projects to enhance your skills in the field of data science and image processing.
Note: In this article, we are going to talk about some ‘low ball’ but really good open-source NLP projects which you can use in your projects. To read more about each of them I recommend following the link given along the project. …
In today’s article, we are going to talk about Six of the open-source custom Object Detection projects to enhance your skills in the field of computer vision and image processing.
Note: In this article, we are going to talk about some of the not-so-famous but really good open-source custom object detection projects which you can use in your projects. To read more about each of them I recommend following the link given along the project.
Bonus
Awesome Object Detection: This is a list of awesome articles about object detection.
Having a good theoretical knowledge is amazing but implementing them in code in a real-time machine learning project is a completely different thing. You might get different and unexpected results based on different problems and datasets. So as a Bonus,I am also adding the links to the various courses which has helped me a lot in my journey to learn Data science and ML. I am personally a fan of DataCamp, I started from it and I am still learning through DataCamp and keep doing new courses. They seriously have some exciting courses. …
Reinforcement learning is an area of machine learning concerned with how intelligent agents ought to take actions in an environment in order to maximize the notion of cumulative reward. Reinforcement learning is one of three basic machine learning paradigms, alongside supervised learning and unsupervised learning. Wikipedia
Reinforcement learning differs from supervised learning in not needing labelled input/output pairs be presented, and in not needing sub-optimal actions to be explicitly corrected. Instead the focus is on finding a balance between exploration (of uncharted territory) and exploitation (of current knowledge)
In this post, you will discover 5 of the best and open-source Reinforcement Learning frameworks and projects available to us. We will review five of the best open-source Reinforcement Learning projects and frameworks available on Github for anyone interested to use it.
If you enjoy reading this article, I am sure that we share similar interests and are/will be in similar industries. So let’s connect via LinkedIn and Github. …
By Mrinal Walia
Life is beautiful, isn't it? Answer for yourself.
Alright, let us recall the moments and events that have led us to believe that the secret to life was indeed “LOVING ONESELF”.
I was in a sad place, dealing with heartbreak, the loss of my friends and family, and work problems. Life wasn't good to me then, and I had reached this tipping point and just when I couldn't take it anymore I decided that I was done living this way and got up and opened my laptop and started writing.
“THIS DAY, I VOW TO MYSELF TO LOVE MYSELF, TO TREAT MYSELF AS SOMEONE I LOVE TRULY AND DEEPLY, AND IN MY THOUGHTS MY ACTIONS THE CHOICES I MADE THE EXPERIENCES I HAD EACH MOMENT I AM CONSCIOUS OF — TODAY I MAKE A DECISION THAT NO MATTER WHAT I LOVE…
Keras is a deep learning API written in Python, running on top of the machine learning platform TensorFlow. It was developed with a focus on enabling fast experimentation. Being able to go from idea to result as fast as possible is key to doing good research.
Keras is a high-level interface and uses Theano or Tensorflow for its backend. It runs smoothly on both CPU and GPU. Keras supports almost all the models of a neural network — fully connected, convolutional, pooling, recurrent, embedding, etc. Furthermore, these models can be combined to build more complex models.
In this post, you will discover 5 of the best and open-source Keras Tensorflow resources available to us. We will review five of the best open-source Keras Tensorflow resources available on Github for anyone interested to use it.
If you enjoy reading this article, I am sure that we share similar interests and are/will be in similar industries. So let’s connect via LinkedIn and Github. …
Human 3D pose estimation is one of the most talked-about or the hottest in recent years and even in the future. Human pose estimation is the process of estimating the configuration of the body (pose) from a single, typically monocular, image. Background. Human pose estimation is one of the key problems in computer vision that has been studied for well over 15 years.
In this post, you will discover 5 of the best and open-source Computer Vision Human-Pose Estimation projects. We will review five of the best open-source Computer Vision Human-Pose Estimation projects available on Github for anyone interested to use it.
BONUS: As a bonus, I am giving a link to the repository with resources on Computer Vision Human Pose Estimation containing papers, codes, articles, tutorials, and many more which can be really helpful with these projects.
* awesome-human-pose-estimation/cbsudux — A collection of awesome resources in Human Pose estimation.
* awesome-human-pose-estimation/wangzheallen — A collection of Human Pose Estimation Related Publication.
If you enjoy reading this article, I am sure that we share similar interests and are/will be in similar industries. So let’s connect via LinkedIn and Github. Please do not hesitate to send a contact request!
Long short-term memory (LSTM) is an artificial recurrent neural network (RNN) architecture used in the field of deep learning. Unlike standard feedforward neural networks, LSTM has feedback connections. It can not only process single data points (such as images), but also entire sequences of data (such as speech or video). For example, LSTM is applicable to tasks such as unsegmented, connected handwriting recognition, speech recognition and anomaly detection in network traffic or IDSs (intrusion detection systems).Wikipedia
A common LSTM unit is composed of a cell, an input gate, an output gate and a forget gate. The cell remembers values over arbitrary time intervals and the three gates regulate the flow of information into and out of the cell.
LSTM networks are well-suited to classifying, processing and making predictions based on time series data.
In this post, you will discover 5 of the best and open-source LSTM Projects. We will review five of the best open-source LSTM Machine Learning projects available on Github for anyone interested to use it.
BONUS: As a bonus, I am giving a link to the article I wrote on Understanding Advanced Modeling in Python: Long Short Term Memory (LSTM) and how to implement LSTM using Python
If you enjoy reading this article, I am sure that we share similar interests and are/will be in similar industries. So let’s connect via LinkedIn and Github. Please do not hesitate to send a contact request! …
The CycleGAN is a technique that involves the automatic training of image-to-image translation models without paired examples. The models are trained in an unsupervised manner using a collection of images from the source and target domain that do not need to be related in any way. This simple technique is powerful, achieving visually impressive results on a range of application domains, most notably translating photographs of horses to zebra, and the reverse.
CycleGAN is an approach to training image-to-image translation models using the generative adversarial network(GANs). The CycleGAN is an extension of the GAN architecture that involves the simultaneous training of two generator models and two discriminator models.
In this post, you will discover 5 of the best and open-source CycleGAN Projects. We will review five of the best open-source CycleGAN Machine Learning projects available on Github for anyone interested to use it.
Having good theoretical knowledge is amazing but implementing them in code in a real-time machine learning project is a completely different thing. …
Python is an interpreted, high-level and general-purpose programming language. Python’s design philosophy emphasizes code readability with its notable use of significant whitespace. Its language constructs and object-oriented approach aim to help programmers write clear, logical code for small and large-scale projects.Wikipedia
Python is dynamically typed and garbage-collected. It supports multiple programming paradigms, including structured (particularly, procedural), object-oriented, and functional programming. Python is often described as a “batteries included” language due to its comprehensive standard library.
In today’s article, we are going to talk about 6 of the best open-source Python Resources available online to get you started with this amazing tool.
Note: In this article, we are going to talk about some of the not-so-famous but really good PythonResources which you can use to make your next projects. To read more about each of them I recommend following the link given along the project.
Having a good theoretical knowledge is amazing but implementing them in code in a real-time machine learning project is a completely different thing. You might get different and unexpected results based on different problems and datasets. So as a Bonus,I am also adding the links to the various courses which has helped me a lot in my journey to learn Data science and ML.I am personally a fan of DataCamp, I started from it and I am still learning through DataCamp and keep doing new courses. They seriously have some exciting courses. …
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