English | Size: 3.85 GB
Genre: eLearning
What you’ll learn
Have a great intuition of many data science models
Make robust data science models
Learn exploratory data analysis
Implement Machine Learning Algorithms
Build machine learning models
“Data science is the transformation of data using mathematics and statistics into valuable insights, decisions, and products”
As data science evolves and gains new “instruments” over time, the core business goal remains focused on finding useful patterns and yielding valuable insights from data. Today, data science is employed across a broad range of industries and aids in various analytical problems. For example, in marketing, exploring customer age, gender, location, and behavior allows for making highly targeted campaigns, evaluating how much customers are prone to make a purchase or leave. In banking, finding outlying client actions aids in detecting fraud. In healthcare, analyzing patients’ medical records can show the probability of having diseases, etc.
The data science landscape encompasses multiple interconnected fields that leverage different techniques and tools.
There’s a difference between data mining and very popular machine learning. Still, machine learning is about creating algorithms to extract valuable insights, it’s heavily focused on continuous use in dynamically changing environments and emphasizes adjustments, retraining, and updating of algorithms based on previous experiences. The goal of machine learning is to constantly adapt to new data and discover new patterns or rules in it. Sometimes it can be realized without human guidance and explicit reprogramming.
Machine learning is the most dynamically developing field of data science today due to a number of recent theoretical and technological breakthroughs. They led to natural language processing, image recognition, or even the generation of new images, music, and texts by machines. Machine learning remains the main “instrument” of building artificial intelligence.
Project-1 Sentiment Analysis App (With Deployment)
Project-2 Attrition Rate Django App
Project-3 App To Find Legendary Pokemon (With Deployment)
Project-4 Face Detection App (Deploy In Streamlit)
Project-5 Cats Vs Dogs Classification App
Project-6 Customer Revenue Prediction App (With Deployment)
Project-7 Gender From Voice Prediction App
Project-8 Restaurant Recommendation System
Project-9 Happiness Ranking App
Project-10 Forest Fire Prediction App
Who this course is for:
Beginners In Data Science
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