# Fundamentals of Machine Learning with Python Implementation.

*Fundamentals of Machine Learning with Python Implementation. Learn Fundamentals of Machine Learning from scratch to make students well equipped with all basics and math involved*

What you'll learn

- Use Python for Data Science and Machine Learning
- Implement Machine Learning Algorithms
- Handle advanced techniques like Dimensionality Reduction
- Know which Machine Learning model to choose for each type of problem
- Basics of Reinforcement Learning
- Linear Regression
- Logistic Regression
- Clustering
- SVM
- Neural Network Concept
- Random Forest
- PCA and SVD

Hello there! Welcome to **Fundamentals of Machine Learning with Python Implementation**.
There are many courses available out there for this domain but what
makes us different is that the learning in this class is gradual. All
the concepts are built from scratch to give students a fair idea of how
various algorithms work in addition to live demonstrations

In
this course, students will acquire a good understanding of basic
concepts of machine learning. The course also introduces students to ** deep learning** (

**) and also**

*neural nets***. The concepts are developed from scratch to make students well equipped with all the basics and math involved with all machine learning algorithms**

*artificial intelligence*Some concepts we cover include

Various types of learning like

**supervised, unsupervised and reinforcement learning.**Various supervised learning algorithms like

**linear and logistic regression.****Clustering techniques.**A brief introduction to

**Neural Nets.**Parameter tuning, data visualization and accuracy estimation techniques

**Reinforcement**learning techniques like**Q-learning**and**SARSA**Deciding which algorithm fits for a given problem

Knowing all of these techniques will give an edge to the developer in order to solve many real world problems with high accuracy.

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