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Top Data Science & Machine Learning Resources – For 2020
If you are aspiring to be a Data Scientist or a Machine Learning Engineer in 2020, you are in the right place. The Journey towards Data Science/Machine Learning is not an easy task however, it is not impossible. You have to be ready for an Intense Hustle to become a “Pro” in Data Science. You can learn Machine Learning and practice well with these resources along with few programming languages like R & Python.
The Top 3 resources that you can use to become a pro in Data Science & Machine Learning
- Andrew ng Machine Learning Course on Coursera
- This is a vast course offered by Stanford University as an online certification course
- Duration: 11 Weeks
- Application Discussed in the course: anti-spam, image recognition, clustering, building recommender systems and more
- List of topics covered in Course:
- Introduction to Machine Learning
- Linear Regression with One Variable
- Linear Regression with multiple Variable
- Logistic Regressions
- Neural Network
- Applied Machine Learning Systems design
- Support Vector Machine Learning
- Unsupervised Learning
- Dimentionality Reduction
- Anomaly Detection
- Recommender Systems
- Large Scale Machine Learnings
2, Fast.AI – Built by machine Learning community to make Machine Learning concept free & easily available to everyone. This is an advanced resource that also includes concepts of Deep Learning.
Below are the resources links:
- Introduction to Machine Learning for Coders
- Computational Linear Algebra
- Code-First Introduction to Natural Language Processing
- Practical Deep Learning for Coders
- Part 2: Deep Learning from the Foundations
3, Kaggle: This is one of the great platforms for all the data science and Machine learning community, where they can work on Solved and Unsolved real-world problems through the competition. Once you are hands-on with concepts Data Analysis, Data Science, Math, Statistics, Algorithms you can pick some simple problem which is already solved to practice. Once you are able to work on multiple easy projects like Titanic Data set or Iris flower data set and more then you can choose to participate in one of the simple kaggle competitions for new Machine Learning Engineers to win some awesome prize money.
These are few of the effective, too technical and more inclined to Applied Machine Learning online courses available. It’s great if you can follow them to keep up the pace of your learning on Data science/ML.
However, these might not directly suit people who are from a different educational background other than computer science and want to pursue Data Science or Machine Learning. You can go through a list of useful resources for Data Scientists/Machine Learning Engineers that are a little simple and easy to understand while covering most of the theory part before you start these courses.