Machine learning is a rapidly developing field with the potential to transform many industries. It can be challenging for a beginner to know where to begin and how to explore the plethora of data available about the subject.

Here are a few simple tips to get you started on your machine-learning path:

1) Begin with the fundamentals:

Before digging into complicated machine learning algorithms, it's critical to first understand the basics. This comprises linear algebra, probability and statistics, and programming topics like data structures and algorithms.

2) Practice with small datasets:

As a newbie, starting with small datasets and basic algorithms might be beneficial. This will give you a better understanding of how the algorithms function and how to evaluate the results.

3) Utilize open-source libraries:

There are several open-source libraries available for machine learning, such as scikit-learn and TensorFlow, that can make it easier for newbies to get started. These libraries include several pre-built algorithms and tools that will assist you to get started right away.

4) Joining a community:

Machine learning is a rapidly expanding area, and there are numerous online and offline communities and organizations that may provide resources and assistance to newbies. Joining a community could help you remain up to speed on the hottest advances in the area, as well as contribute and benefit from others' knowledge.

5) Engage with real-world projects:

Practicing with real-world projects is the finest approach to developing a taste for machine learning. This will assist you in learning how to apply the algorithms to real-world issues and develop a better knowledge of the subject.

6) Don't hesitate to seek help:

Machine learning may be an advanced, powerful, and demanding area, so don't be afraid to seek assistance. Multiple resources can help you succeed, whether you're stuck on a particular problem or simply want to understand more regarding a particular topic.

To conclude, machine learning is a wide and fascinating area with a lot of opportunities. As a newbie, it's critical to start with the fundamentals, experiment with small datasets, use open-source libraries, and get involved in a community. Also, don't be reluctant to seek support when you require it. You'll be well on your way to becoming a machine learning expert if you follow these guidelines.

Free Youtube resources:

1. Stanford CS229: Machine Learning

2. MIT: Introduction to Deep Learning

3. Machine Learning Specialization

4. Lex Fridman's MIT Deep Learning

Some best free online courses

1. All Machine Learning courses by Fast.ai

2. NYU Deep Learning course by Yann Lecun

3. Harvard's Artificial Intelligence course

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