What type of data science projects you can work on?

Top Data Science Project Ideas

• 1.1 Fake News Detection.
• 1.2 Road Lane Line Detection.
• 1.3 Sentiment Analysis.
• 1.4 Detecting Parkinson’s Disease.
• 1.5 Color Detection with Python.
• 1.6 Brain Tumor Detection with Data Science.
• 1.7 Leaf Disease Detection.

What are some cool data science projects?

List of 10 interesting data science projects ideas to boost your career growth in data science.

• Chatbots.
• Credit Card Fraud Detection.
• Fake News Detection.
• Forest Fire Prediction.
• Classifying Breast Cancer.
• Sentiment Analysis.
• ColorDetection.
• Driver Somnolence Detection.

How data science is used in retail industry?

In data science, recommendation systems proved to be of great use for the retailers as the tools for customers’ behavior prediction. It helps to gain the customer opinion of any particular product. Providing recommendations enables retailers to increase sales and to dictate trends.

How Analytics is used in FMCG industry?

One way that FMCGs are using big data in supply chain analytics is to optimize delivery networks. Organizations across the sector have been using analytics to merge multiple delivery networks to create a faster, more streamlined process.

How do projects work in data science?

Let’s look at each of these steps in detail:

1. Step 1: Define Problem Statement. Before you even begin a Data Science project, you must define the problem you’re trying to solve.
2. Step 2: Data Collection.
3. Step 3: Data Cleaning.
4. Step 4: Data Analysis and Exploration.
5. Step 5: Data Modelling.
6. Step 6: Optimization and Deployment:

What constitutes a data science project?

A data science project covers a whole host of data-related roles, such as a data engineer, machine learning engineer, deep learning engineer, business analyst, data analyst, etc. The list goes on. A Data Scientist doesn’t build architecture for a big data system – a data engineer does.

What are some good big data projects?

Big Data Project Ideas: Advanced Level

• Big Data for cybersecurity.
• Health status prediction.
• Anomaly detection in cloud servers.
• Recruitment for Big Data job profiles.
• Malicious user detection in Big Data collection.
• Tourist behaviour analysis.
• Credit Scoring.
• Electricity price forecasting.

How do Data Science projects work?

In this article, I am going to share step by step guide on how to start a personal project.

1. Step 1: Identify a Real-World Problem to Solve. Find your own itch.
2. Step 2: Decide which dataset to work on.
3. Step 3 Perform analysis and modeling.

How big data is applied in the retail industry?

Big Data provides retailers opportunities to enhance their customer experiences. Big Data Analytics will help retailers in anticipating a customer’s demand and therefore would empower them in taking effective and customer-centric decisions and thus personalizing their marketing based on consumer data.

What is FMCG data?

FMCG stands for Fast Moving Consumer Goods refers to organizations that provide products in large quantities. These products are generally inexpensive, the volumes sold are large and might usually have a short shelf life. Most FMCG companies are not lacking in data from a wide range of sources.

What are supply chain analytics?

Supply chain analytics is the analysis of information companies draw from a number of applications tied to their supply chain, including supply chain execution systems for procurement, inventory management, order management, warehouse management and fulfillment, and transportation management (including shipping).

How machine learning and data science are transforming the FMCG industry?

The solution is Data Science and Machine Learning. With the help of advanced machine learning algorithms, the FMCG company can merge all the data and bring structure to it, and therefore find better answers to various problems that plague their business.

What are the challenges faced by FMCG companies in decision making?

At every stage of this journey from manufacturing to delivery to marketing and sales, an FMCG company faces several challenges in decision making and the only resource that can be relied upon is data.

What are the most efficient data science use cases in construction?

Let’s take into consideration several of the most efficient and productive data science use cases in the construction industry. One of the most fundamental data science use cases is prediction. Predictive analytics has taken under its control the analysis of vast amounts of data providing the capability to forecast.

What is the role of FMCG in the retail industry?

The FMCG companies try to out-do one another in production, supply chain, sales, marketing and retail strategies in bringing to us on the store shelf, fast-moving inexpensive products that may often have a low shelf life.