Solved end-to-end Data Science Projects in Python

Solved
end-to-end
Data Science Projects in Python

Get ready to use coding projects for solving real-world business problems

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Data Science Projects in Python

 

PySpark Project-Get a handle on using Python with Spark through this hands-on data processing spark python tutorial.

Machine Learning Project - Work with KKBOX's Music Recommendation System dataset to build the best music recommendation engine.

Deep Learning Project- Learn to apply deep learning paradigm to forecast univariate time series data.

In this data science project, we will predict the credit card fraud in the transactional dataset using some of the predictive models.

In this machine learning pricing project, we implement a retail price optimization algorithm using regression trees. This is one of the first steps to building a dynamic pricing model.

In this machine learning churn project, we implement a churn prediction model in python using ensemble techniques.

In this NLP AI application, we build the core conversational engine for a chatbot. We use the popular NLTK text classification library to achieve this.

In this machine learning resume parser example we use the popular Spacy NLP python library for OCR and text classification.

In this Kmeans clustering machine learning project, you will perform topic modelling in order to group customer reviews based on recurring patterns.

In this human activity recognition project, we use multiclass classification machine learning techniques to analyse fitness dataset from a smartphone tracker.

In this data science project, you will learn how to perform market basket analysis with the application of Apriori and FP growth algorithms based on the concept of association rule learning.

Text data requires special preparation before you can start using it for any machine learning project.In this ML project, you will learn about applying Machine Learning models to create classifiers and learn how to make sense of textual data.

Use the Amazon Reviews/Ratings dataset of 2 Million records to build a recommender system using memory-based collaborative filtering in Python.

In this supervised learning machine learning project, you will predict the availability of a driver in a specific area by using multi step time series analysis.

This project analyzes a dataset containing ecommerce product reviews. The goal is to use machine learning models to perform sentiment analysis on product reviews and rank them based on relevance. Reviews play a key role in product recommendation systems.

Data Science Project in Python- Build a machine learning algorithm that automatically suggests the right product prices.

Data Science Project in Python- Given his or her job role, predict employee access needs using amazon employee database.

This data science in python project predicts if a loan should be given to an applicant or not. We predict if the customer is eligible for loan based on several factors like credit score and past history.

The goal of this data science project is to build a predictive model and find out the sales of each product at a given Big Mart store.

There are different time series forecasting methods to forecast stock price, demand etc. In this machine learning project, you will learn to determine which forecasting method to be used when and how to apply with time series forecasting example.

In this machine learning project, we will use binary leaf images and extracted features, including shape, margin, and texture to accurately identify plant species using different benchmark classification techniques.

In this project, we are going to talk about Time Series Forecasting to predict the electricity requirement for a particular house using Prophet.

In this data science project, we will predict internal failures of Bosch using thousands of measurements and tests made for each component along the assembly line.

In this machine learning project, we will build a predictive model to find out the sales of each product at a particular store.

In this data science project with Python, we will complete the analysis of what sorts of people were likely to survive.You will learn to use various machine learning tools to predict which passengers survived the tragedy.

In this machine learning project , you will predict the total travel time of taxi trips from their initial partial trajectories.

Using this Kaggle dataset, you will explore which type of employees make less or more money, or which employees get normal pay hikes and promotions.

The goal of this data science project is to take an image of a handwritten single digit, and determine what that digit is.

Build a predictive model to correctly classify products between 9 product categories (fashion, electronics, etc.) using the Otto Group dataset.

Build a machine learning model that will predict which jobs users will apply to given their past applications, demographics and work history.

Forecast the business for the upcoming years by Exploring Hidden Trends, Calculating Machine Productivity , Extrapolation and Assumptions and Summarizing Answers through Visualizations.

Data Science Project-Predict the car insurance policy a customer buys after receiving a number of quotes.

Given a customer's search query and the returned product in text format, your predictive model needs to tell whether it is what the customer was looking for.

In this data science project, you will contextualize customer data and predict the likelihood a customer will stay at 100 different hotel groups.

In this data science project, you will be working on building a machine learning model that can identify nerve structures in a data set of ultrasound images of the neck. This will help enhance catheter placement and contribute to a more pain free future.

In this machine learning project you will work on creating a robust prediction model of Rossmann's daily sales using store, promotion, and competitor data.

In this machine learning project, you will build a model to predict the purchase amount of customer against various products which will help the company create personalized offer for customers against different products.

The goal of this machine learning project is to predict which products existing customers will use next month based on their past behaviour and that of similar customers.

In this project, we will automate the loan eligibility process (real-time) based on customer details while filling the online application form.

In this data science project, we will look at few examples where we can apply various time series forecasting techniques.

In this data science project, we will predict the number of inquiries a new listing receives based on the listing's creation date and other features.

The goal of this NLP project is to predict which of the provided quora question pairs contain two questions with the same meaning.

Deep Learning Project using Keras Deep Learning Library to predict the effect of Genetic Variants to enable personalized Medicine.

In this project, we will build a model to predict the purchase amount of customers against various products which will help a retail company to create personalized offer for customers against different products.

In this machine learning project, we will implement Back-propagation Algorithm from scratch for classification problems.

In this project, we will use traditional time series forecasting methods as well as modern deep learning methods for time series forecasting.

In this project, we are going to predict how capable each applicant is repaying a loan.

In this project, we are going to talk about insurance forecast by using regression techniques.

The Value of Data Science Projects for Data Science Beginners/Data Enthusiasts

When you are completely new to learning data science, it’s natural to focus on what and how you need to learn to become a successful data scientist in the industry. But no e-learning provider, offline or online, has information that you cannot find using Google or in a top data science book. There isn’t a secret stash of real-world industry data science knowledge that educators are keeping behind their paywalls. Most e-learning providers often attempt to work hard in providing the best, most useful, and concise data science knowledge and package it into a neat bundled comprehensive data science course. However, that’s not where most learning value is to be found when it comes to mastering data science and machine learning. If we had to put a number on it, we would say 10% of the value comes from data science courses while 90% of the value comes from working on interesting data science projects. By working through lots of diverse data science project ideas, you can transform your theoretical data science knowledge into hands-on data science skills and real industry-level proficiency.

Here at ProjectPro, we believe that working on interesting data science project briefs is a deeply valuable method of learning data science. ProjectPro enables you to seek technical support from industry experts to progress much more quickly than if you were working alone on a data science project.

How ProjectPro’s Python Data Science Projects can help you learn data science?

One of the hardships of learning any skill, data science included, is that you often repeat the things you already know how to do. For example, anyone learning to play a keyboard often plays the music notes on the first page again and again because it feels good to hear the right notes. But, that time can be better spent learning the music notes on the pages he didn’t know at all. A data scientist who only practices the skills they already know is going to have difficulty to improve anytime soon. The secret sauce to improvement, is, of course, to practice data science techniques you don’t know how to implement. Data science projects are valuable learning tools because they’ve been designed by constraints that you have not set yourself. Where a data science project demands data science skills that you don’t yet have, you are forced to seek out extra knowledge and cultivate those data science skills. By forcing you to learn about new data science techniques, tools, and technologies through projects, you’re made to expand your knowledge and grow in confidence. 

Data science projects let you produce extra versions of your model (“iterations”) to achieve a more refined, optimized, and accurate result. On completing a project, the iterative process of building machine learning models lets you look back on how you reached from A to Z of model building and reflect on the steps you took along the data science project workflow. This reflection is itself a crucial data science skill that maximizes one’s learning from each data science and machine learning project and sharpens your critical thinking skills. Reflecting at the end of a data science project helps you understand why you applied a specific machine learning algorithm or why you tuned the parameters for a specific model, so you can consolidate your new knowledge in data science. 

 For data science beginners, it is difficult to self-critique their own model. This is because beginners don’t yet have enough bank of experience and data science knowledge that helps them evaluate their own machine learning models. However, working with diverse datasets on interesting data science project ideas across different business domains will allow them to see a range of different data science solutions to the same kind of business problem. This will make data science beginners eye keener as they begin to identify the pros and cons of each modeling approach.

One of the happy side-effects of learning data science through projects is that you can easily produce the contents for a winning data science portfolio which is what many employers want to see. Hiring managers are on the lookout for specific data science skills for any data scientist job.  Balancing a data science portfolio with different data science projects helps showcase hiring managers that you have a diverse data science skillset.

 Last but not least, the most enjoyable part of learning data science through projects is that you are constantly completing various data science tasks like data cleaning, data munging, data visualization, data storytelling, and improving your skill set. On completing data science projects when you take a step back you will feel pride in what you’ ve accomplished and feel-good. Checking data science skills off your list motivates you to do more projects! 

Why should you work on ProjectPro’s Data Science Projects in Python?

Who should work on ProjectPro’s Python Data Science Projects?

Key Learnings from ProjectPro’s Data Science Projects in Python

Data Science Projects for Beginners with Source Code in Python

Here are our industry expert panel recommendations on some cool and interesting python data science projects for beginners –

1) Build a Chatbot from Scratch in Python using NLTK

2) Churn Prediction in Telecom

3) Market Basket Analysis using Apriori

4) Build a Resume Parser using NLP -Spacy

5) Model Insurance Claim Severity

6)Sentiment Analysis of Product Reviews

7) Loan Default Prediction 

8) Build an Image Classifier Using Tensorflow

9) PUBG Finish Placement Prediction

10) Price Recommendation using Machine Learning

11) Fraud Detection as a Classification Problem

12) Sales Forecasting

13) Building a Recommender System

14) Employee Access-Challenge as a Classification Problem

15) Survival Prediction using Machine Learning

What will you get when you enroll for ProjectPro’s Data Science Mini Projects in Python?

There are tons of cool and interesting data science project ideas that one can create and are not limited to what we have listed. ProjectPro’s python data science projects will help you implement your imagination in building data products using python language. Drop us an email at khushbu.shah@dezyre.com if you require or would be interested to work on any other kind of dataset. We will try to help you at our best.