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I will do machine learning and data science tasks and projects for you


I will do machine learning and data science tasks and projects for you

Machine learning (ML) and Data Science (DS) projects are hard to manage. Because projects are research-like in nature, it’s difficult to predict how long it will take for them to finish

Get  machine learning and data science tasks and projects

Machine learning and data science are two of the most popular fields in computer science today. There are many tasks and projects that can be done in these fields. Some of the most common machine learning tasks include classification, regression, clustering, and anomaly detection. Data science tasks include data cleaning, data visualization, and data analysis.

There are many projects that can be done in these fields as well. Some examples of machine learning projects include image recognition, natural language processing, and recommendation systems. Data science projects include predictive modeling, customer segmentation, and market basket analysis.

If you’re interested in learning more about these fields and the types of tasks and projects that can be done in them, there are many resources available online. You can find tutorials, courses, and other resources that will help you get started with machine learning and data science.

Data science is a field that studies data and how to extract meaning from it, whereas machine learning is a field devoted to understanding and building methods that utilize data to improve performance or inform predictions. Machine learning is a branch of artificial intelligence1.

Machine learning is a hybrid of data science and machine, while data science mainly involves analytics and statistics. Machine learning only focuses on algorithms statistics, while data science focuses on many more aspects of data rather than just algorithm statistics2.

In summary, data science is the all-encompassing rectangle, while machine learning is a square that is its own entity. They are both often used by data scientists in their work and are rapidly being adopted by nearly every industry1.

There are many resources available online to learn machine learning. Here are some of the best ones:

  1. All Machine Learning courses by Fast.ai - Free Courses
  2. NYU Deep Learning course by Yann Lecun - Deep Learning
  3. Harvard’s Artificial Intelligence course - Introduction to AI with Python
  4. Scikit-Learn is a scientific Python library for machine learning. The best resource I found for this so far is the book “Hands on Machine Learning with Scikit-Learn and Tensorflow”1.
  5. Udacity’s nano-degrees are 3 to 6 month courses, with plenty of practice and a good, concise portion of theory to back up practical skills2.

There are many resources available online to learn data science. Here are some of the best ones:

Data Science Essentials - Microsoft Professional Program Certificate
Data Science Methodology - IBM Professional Certificate
Applied Data Science with Python - University of Michigan on Fiverr
Data Science Fundamentals - IBM on Coursera
Data Science Specialization - Johns Hopkins University on Fiverr

There are many resources available online to learn machine learning. Here are some of the best ones:
  • All Machine Learning courses by Fast.ai - Free Courses1
  • NYU Deep Learning course by Yann Lecun - Deep Learning1
  • Harvard’s Artificial Intelligence course - Introduction to AI with Python1
  • Scikit-Learn is a scientific Python library for machine learning. The best resource I found for this so far is the book “Hands on Machine Learning with Scikit-Learn and Tensorflow”2.
  • Machine Learning Specialization on Coursera - University of Washington3