Meet Mandaviya's Projects
Having multiple attributes like Make, Model, Type, Origin, MRP, Engine Size, and Mileage, the cars dataset formed the basis of my approach. I initiated the process with basic analysis and later utilized various operations to solve the questions posed in the dataset.
The Covid_19 dataset contains information on regions, confirmed cases, deaths, and recovered cases. After conducting preliminary data analysis (EDA), I proceeded to address the questions.
Performing NLP sentiment analysis on Disneyland reviews, uncovering emotions and opinions from visitors. Gaining insights into overall satisfaction and areas for improvement in the park experience.
A powerful NLP model to classify sentiments in hotel reviews. Accurate, user-friendly, and ready-to-use for analyzing customer feedback and improving hospitality services.
After conducting Exploratory Data Analysis on the India census dataset, I proceeded to respond to the given questions.
Having received the London Housing dataset, I initiated the process by performing initial analysis and subsequently employed different techniques to address the questions given in the dataset.
Let's take a look at a scenario where we can recognize different items of clothing, trained from a dataset containing 10 different types.
You'll try to build a neural network that predicts the price of a house according to a simple formula.
I've done sentiment analysis on IMDB movie reviews, distinguishing positive and negative opinions. Unveiling insights into audience perceptions, helping comprehend movie reception and feedback.
A multitude of questions are provided; at first, I conducted preliminary data analysis using basic functions, and later, I tackled all the questions.
Digit recognition dataset for CNN. Contains handwritten numbers. Employed with a Sequential ML model, achieving accurate classification of digits through deep learning techniques.
Titanic dataset for survival prediction. Analyzed with various ML models. Unveils passenger survival patterns through distinct algorithms, providing insights into the disaster's impact on different groups.
Initially, I conducted Exploratory Data Analysis (EDA) before delving into the question using this dataset.
The weather dataset was given, and my approach involved starting with basic analysis before applying various operations to solve the questions posed in the dataset.
Explore the Zomato dataset through insightful EDA analysis. Uncover restaurant trends, cuisines, ratings, and customer preferences. Discover hidden patterns and make data-driven decisions in the food industry. Gain valuable insights into dining habits and more