Machine Learning in Python

What do you like best about machine-learning in Python?

- Makes Data Preparation and exploration easy, specially at initial stage

- No need for data extraction. Can work with the data in DB

- Pipeline is simple

What do you dislike about machine-learning in Python?

- Limited algorithms supported

- Cost, due to license

What problems is machine-learning in Python solving and how is that benefiting you?

Python is ver popular language now. While keeping data in DB, no need for extraction steps, we can do complete POC for supervised, classification, bag of words, ... solutions for data in DB.

Without doing ETL, we currently are able to do some supervised learning solutions for data in Oracle DB using OML4Py

What do you like best about machine-learning in Python?

The thing I like best about machine learning with python is it provides extensive libraries and framework which make our work easy. It's has one of the best community support for coders.

Best for visualization with help of Matplotlib as Seaborn...

What do you dislike about machine-learning in Python?

Currently there is nothing which I see I dislike about machine learning with python.

What problems is machine-learning in Python solving and how is that benefiting you?

Machine learning in Python has addressing a wide range of problems across various domains, and its benefits are substantial in fields like finance, Healthcare, manufacturing production and nature language processing and also transportation...

What do you like best about machine-learning in Python?

Since Python is a very easy langauge and for machine learning, we have to write a large, diverse, and very complex code which is quite difficult in any other programing language so from that point python is the best suitable language for machine learning. Also, it has huge libraries that help developers to write code efficiently and effectively.

What do you dislike about machine-learning in Python?

As a machine-learning engineer, I have found Python to be an amazing machine-learning language, and I value its adaptability and breadth of features. Python is well-known not only for its success in machine learning and data science but also as a top choice for web development and other disciplines. Its extensive library ecosystem, user-friendly syntax, and lively community make it a favorite language for developers, enabling them to design new and efficient solutions. Python actually shines at providing a smooth and engaging experience for both machine learning practitioners and fans.

What problems is machine-learning in Python solving and how is that benefiting you?

The use of machine learning in Python has contributed to the creation of powerful tools and libraries that have enabled the development of more advanced and sophisticated AI models like chat gpt. It provides efficient and scalable solutions to complex problems, helps in automating tasks, enhances decision-making processes, enables data-driven insights, and opens up opportunities for innovation and competitive advantage. Python's rich ecosystem of libraries, extensive documentation, and active community further support practitioners in building and deploying machine learning models effectively.

What do you like best about machine-learning in Python?

Pandas - I love to explore the data with pandas

What do you dislike about machine-learning in Python?

At times simple task we need to follow the sane steps

What problems is machine-learning in Python solving and how is that benefiting you?

Predictions

What do you like best about machine-learning in Python?

One of the key benefits of using Python for machine learning is its ease of use. The language has a clean and intuitive syntax that makes it easy to write and understand code, even for those who are new to programming. Additionally, Python has a large and supportive community that provides plenty of resources and tutorials to help users get started.

What do you dislike about machine-learning in Python?

Python is an interpreted language, which means that it is slower than compiled languages like C++ or Java. This can be a disadvantage when working with very large datasets or complex algorithms.

What problems is machine-learning in Python solving and how is that benefiting you?

With the help of Python Machine learning it can be used to detect fraudulent transactions, such as credit card fraud. Python libraries such as sci-kit-learn and TensorFlow is used to build fraud detection models that can identify patterns of fraudulent behavior.