Pranavd0828

GeometricBrownianMotion

Applying Geometric Brownian Motion (GBM) - Financial Modeling

SBA-LoanApproval-Predictve-Modeling

Applying predictive modeling to the SBA National Dataset

BasicNeuralNetwork_Keras_Prediction

Applying Keras to conduct basic neural networking on Sales Data

CorrelationBased_RecommendationSystem

The repository prompts the user to select the recommendation approach, user-based (correlation). Based on the selected approach and similarity metric, this function predicts the rating for specified user and item and also suggests if the item could be recommended to the user.

GooglePlayStore_Ratings_Predictive_Modeling

Predictive modeling for Google App Rating

NIFTY50-StockMarket

NLP_SpamMsg_Analysis

Analyzing Spam messages using Natural Language Processing (NLP)

Predictive_Modeling_Tropicana_RetailPrice

Conducting Predictive modeling on Tropicana data to predict Optimal Pricing

DigitalAd_DataAnalysis

Applying Data Modeling on fortune 500 Companies' data

LogisticRegression_on_Titanic_dataset

Applying Logistic Regression on Titanic Dataset

RealEstate_DataAnalysis

Applying data modeling on the RealEstate data

Sketching_Image

Converting input image to hand drawn sketch image

Basic_of_RegularExpression

Regular expressions (called REs, or regexes, or regex patterns) are essentially a tiny, highly specialized programming language embedded inside Python and made available through the re module. Using this little language, you specify the rules for the set of possible strings that you want to match; this set might contain English sentences, or e-mail addresses, or TeX commands, or anything you like.

Basic_PyTorch_and_MNIST

Exploring Torch library in Python

ClassificationBased_CollaborativeFiltering

Applying Classification based Collaborative Filtering- Recommendation Model

ContentBasedRecommendation_System

Content-based filtering uses item features to recommend other items similar to what the user likes, based on their previous actions or explicit feedback. I have applied basic content-based recommendation system using python.

Face_Identification_F.R.I.E.N.D.S

Detecting faces in an image

LeetCode_Practice

Some LeetCode questions with Easy, Medium, Hard labels

Lyft_RiderCancellation_EDA

Investigated Lyft riders’ data set, by performing data wrangling, conducting exploratory data analysis, and building statistical machine-learned model, using python packages, to determine KPIs, that guide riders’ cancellation decision

Market_Forecasting_in_Excel

Conducting Market Forecasting using Excel with different modeling algorithms.

ModelBased_RecommendationSystem

Model-based recommendation systems involve building a model based on the dataset of ratings. This approach potentially offers the benefits of both speed and scalability. [Source: http://www.cs.carleton.edu/cs_comps/0607/recommend/recommender/modelbased.html]

my-first-binder

Open-Asteroid

Dataset about the most updated asteroids along with their updated features

Pendulum_Simulation

Using animation in python to implement different pendulum

PopularityBased_RecommendationSystem

As the name suggests Popularity based recommendation system works with the trend. It basically uses the items which are in trend right now.

PythonMatrix_Operations

Fundamental Array and Matrix operations using Python

SudokuSolver_ML

Designed neural network to gain context about the vacant positions in Sudoku.Also implemented Naked Twins approach to create a Sudoku Solver.