Instructors: Pianalytix .76 sections 553 lectures 73h 33mVideo: MP4 1280x720 44 KHz | English + SubUpdated 2/2022 | Size: 34 GB

Solve business problems using data science, machine learning practically and build real world projects using python
What you'll learn
Clean your input data to remove outliers
Implement Machine Learning Algorithms
How to improve your Machine Learning Models
Make robust Machine Learning models
Master Machine Learning on Python
Requirements
Basic knowledge of machine learning
Description
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 , 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 chag 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. Somes 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.
Who this course is for
Bners in data science




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