kavilivishnu Goto Github PK
Name: Kavili Sri Vishnu Vardhan
Type: User
Company: XOPA Ai
Bio: def alive(): print("wake up, code") alive()
Location: Gachibowli, Hyderabad
Name: Kavili Sri Vishnu Vardhan
Type: User
Company: XOPA Ai
Bio: def alive(): print("wake up, code") alive()
Location: Gachibowli, Hyderabad
This is a Chat App with no Back-end server. Coded only with the help of React Hooks and REDUX. The App consists of almost all the attributes that are in common to WhatsApp's. Such as: 1)Tag a message and Reply to it 2) Indication of Message Seen 3) Delete For Me and 4) Delete For Everyone.
A Deep Learning Project on "Sentiment Analysis". We will be training and testing our model on the reviews that we get from the reviews, which are from the IMBD Dataset. We will also check "ONE POSITIVE" and "ONE NEGATIVE" review that our model classifies correctly, the other such testing methods
A Deep Learning Project on "IMAGE DETECTION" using MNIST and FASHION MNIST datasets. We will be using many combinations of activation fucntions, loss and other normalization techniques to show how the accuracy improves if certain parameters are added to the netwrok and many such implementations.
The main concentration of this project lies on image calssification using traditional CNN(Convolution Neural Networks), and also a couple of "BASE MODELS" such as "RestNet50", "DenseNet121" and "EfficientNetB0" that upgraded the performance of our CNN, followed by the Fully Connected NN, that we are using to train our model on.
The data in this application is rendered through a mock interview requests API, and a custom-made toggle button helps in mapping the data as per our needs. A convenient filter while searching function had been fit into the application too. Accomplished with React hooks alone.
Integrating OpenAI's LLM - GPT-4 and NLTK, I have created a small conversation feature. Leveraging OpenAI's power, I have fetched response for a prompt. Then extracting some important features from the description, I have generated a question template. This questions are again posted to OpenAI, which gives back a response to it.
A Deep Learning Project on "Multi-Category analysis" using news articles from the Reuters news agency. With this classification within categories of categories, we can understand the textual data. We used algorithms such as ""One-Hot-Encoding", and many other features to improve our models perrformance.
A starter and basic project on cGANs(Conditional Generative Adversarial Networks). Leveraging the cGANs ability to predict the "Progression of the Shape" of the cell. I have used some important attributes such as Cell's Life cyle stage, Mitotic Index, DNA Content and many such to "Generate" it's shape after a "6-HOUR Time Delta"
The React documentation website
A Deep Learning Project on "Regression" using the Boston Housing Prices dataset. We used algorithms such as "k-fold", which will help us in getting more combinations if training and testing sets, which will give a robust performance of our model. Many other features are included to improve our models perrformance.
A simple and basic Shopping Application which has all the required attributes that a shopping website has to offer. Implemented using REDUX with React Hooks. You can view the App with help of the link provided in the README.md section.
This Computer Vision project is about training our model to accurately identify the House Numbers that are captured by the Google Street View. I have used the SVHN dataset to accomplish this task. Leaveraging some refined structure of the Layers of our Network, I was able to acheive good accuracy.
A complete Python code used for "vectorizing" the given documents, and givng the "Cosine-Similarity" between the given documents.
This App let's you keep track of all the money that you've spent during a trip, any other expenses etc.. It also gives you the total amount of your expenses.
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