Need Learning Roadmap for Machine Learning and Data Science

Question

Hi All!

I wanted to understand how to go with Machine Learning and Data Science, need your sugessions. If is their any resources availbe which can guide would be helpful.

Any sugeestion about this - will this have future.

Being an writer I believe, writting is easy than learning programming...hahahahah

Thanks!

Answer 1

Machine learning and data science are both rapidly growing fields with a ton of potential. Here's a breakdown to get you started:

Learning Path:

• Foundational Skills: Brush up on your math, particularly statistics and probability. These are crucial for understanding machine learning algorithms. You'll also need to learn a programming language, with Python being the most popular choice due to its extensive data science libraries. SQL is another useful skill to have, as it allows you to query and manipulate databases.
• Machine Learning: Once you have the basics down, delve into core machine learning concepts. There are many online courses and resources available, some even offered by universities like Harvard [1]. These will introduce you to popular algorithms, techniques for data preparation and model evaluation.

Resources:

• Online Courses: Platforms like Coursera, edX, and Udacity offer a wide range of data science and machine learning courses [1, 2].
• Books: Several books cater to beginners, such as "Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow" by Aurélien Géron.
• YouTube Channels: Many YouTubers explain machine learning concepts in an engaging way, with channels like Krish Naik and 3Blue1Brown being popular choices [YouTube].

Future of Machine Learning and Data Science:

The future of these fields is incredibly bright! Machine learning and data science are already transforming various industries, and their applications will only continue to grow. So yes, there's immense potential for a fulfilling career.

Writing vs. Programming:

While writing is a valuable skill, programming is becoming increasingly important across many fields. Data science combines both technical and analytical aspects, so you can leverage your writing skills to communicate complex findings in a clear and concise way.

Remember, the key is to start strong and be persistent. Don't be discouraged if you find programming challenging at first. There are many resources available to help you on your journey!

Answer 2

Thank you for your concise response, @Jithu Thomas; it will undoubtedly assist me in getting started. I have reviewed the Coursera and edX courses, and I can confidently say they are of good enough to start. Before enrolling in any courses, I believe I should first follow a roadmap. I found an ML roadmap (https://www.scaler.com/blog/machine-learning-roadmap/) to see if I can understand the topics mentioned in it. I am considering giving myself a month before I opt for any courses. Thanks for the advice.

Answer 3

Hi!

If you're interested in getting started with Machine Learning and Data Science, there are various resources available to guide you. Here are a few suggestions:

1. Online Courses: Platforms like Coursera, edX, and Udemy offer a wide range of courses on Machine Learning and Data Science. Popular courses include Andrew Ng's "Machine Learning" course on Coursera and the "Introduction to Data Science in Python" course on edX.

2. Books: There are many books available that cover the fundamentals of Machine Learning and Data Science. Some popular titles include "Hands-On Machine Learning with Scikit-Learn and TensorFlow" by Aurélien Géron and "Python for Data Analysis" by Wes McKinney.

3. Online Tutorials and Blogs: Many websites and blogs provide tutorials and articles on Machine Learning and Data Science. Some popular ones include Towards Data Science, Kaggle, and Analytics Vidhya. These resources often offer practical examples and code snippets to help you learn.

4. Online Communities: Participating in online communities like Reddit's r/MachineLearning or joining Data Science forums can provide opportunities to connect with other learners and professionals in the field. You can ask questions, share ideas, and learn from others' experiences.

As for the future of Machine Learning and Data Science, it is a rapidly growing field with a lot of potential. The demand for professionals with skills in these areas is increasing across industries. With advancements in technology and the increasing availability of data, the applications of Machine Learning and Data Science are expected to expand further.

Regarding your comment on writing being easier than learning programming, it's true that programming can have a learning curve, but with dedication and practice, it can become easier over time. Writing and programming are different skills, but both require practice and continuous learning to improve. So, don't be discouraged and keep exploring and learning!

I hope these suggestions help you get started on your journey into Machine Learning and Data Science. Good luck!