How To Learn Machine Learning In 2024 | Machine Learning Roadmap | 2024 | Simplilearn

Sep 2, 20240 likes116 views

In this video on how to learn Machine Learning in 2024, covering everything you need to get started and excel in this exciting field. We begin with a clear explanation of what Machine Learning is and why it matters. Then, we guide you through the essential programming language, Python, and the importance of mastering Version Control Systems. You'll also learn about key Data Structures and Algorithms, SQL for managing data, and the crucial Mathematics and Statistics that underpin Machine Learning models.

How To Learn Machine Learning In 2024 | Machine Learning Roadmap | 2024 | Simplilearn

What is Machine Learning?
Machine Learning is a type of Artificial Intelligence(AI) that allows
computers to learn from data and make decisions without being programmed
for each task explicitly.

Roadmap to learn Machine
Learning
Programming Languages
01
Python for its
extensive libraries like
NumPy, Pandas.
R language for its
statistical computing
and data
visualization.

Roadmap to learn Machine
Learning
Version Control System
02
 git
commit
 git add
 git merge
 git status
 git config
 git push
 git pull
 git clone <path>
 git reset

Roadmap to learn Machine
Learning
Data Structures and Algorithms
03
• Arrays
• Linked
List
• Stack
• Trees
• Queue

Roadmap to learn Machine
Learning
Structured Query
Language(SQL)
04
Accessing data and organizing them are necessary for your
model.

Roadmap to learn Machine
Learning
Mathematics and Statistics
05
• Linear
Algebra
• Probabili
ty
• Statistics • Calculus

Roadmap to learn Machine
Learning
Data Handling
06
Python data handling includes creating, reading and writing
to files.
Listing files from
directory.
Copy and delete directories.
Copy ,rename and delete files from
directories

Roadmap to learn Machine
Learning
Machine Learning
Fundamentals
07
Supervised Learning. Unsupervised Learning.
Python Libraries

Roadmap to learn Machine
Learning
Advanced Machine learning
Concepts
08
Natural Learning
Process(NLP)
Computer Vision
Deep Learning
Ensemble Learning

Roadmap to learn Machine
Learning
Model Deployment
09
Setting models into action is the final step.
Python Frameworks

The document discusses the most basic Python libraries for machine learning. It covers libraries for data gathering (Beautiful Soup, Requests, Pandas), data cleaning (NumPy, Pandas), exploring data (Seaborn, Matplotlib.pyplot, Pandas), building models (SciKit-learn, Statsmodels), and visualization (Seaborn, Matplotlib.pyplot, Plotly, Geoplotlib). Beautiful Soup is for parsing HTML/XML, Requests makes HTTP requests, Pandas handles data structures, NumPy provides scientific computing tools. Seaborn and Matplotlib create plots and visualizations. SciKit-learn has machine learning algorithms. Statsmodels fits statistical models.

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