Ementorhub

Skills you'll gain

Python Programming

Regression Analysis

Machine Learning Methods

Data Processing

Matplotlib

Deep Learning

Network Model

Pandas (Python Package)

Data Science

Tensorflow

Keras (Neural Network Library)

Artificial Intelligence and Machine Learning (AI/ML)

Data Manipulation

Artificial Neural Networks

NumPy

There are 17 modules in this course

Learn Python basics focused on data science, and master tools like Matplotlib, NumPy, and Pandas for data cleaning and visualization. Progress from the MP Neuron model to the Perceptron, Sigmoid Neuron, and Universal Approximation Theorem, exploring ReLU and SoftMax activation functions. Gain practical experience with TensorFlow 2.x, creating and training deep neural networks, evaluating their performance, and fine-tuning for optimal results. By the course's end, you'll be on your way to becoming a deep-learning expert. This beginner-friendly course is perfect for students and professionals aiming to stay updated on AI. A basic understanding of programming is recommended but not required, as foundational Python skills are covered in the course.

Getting the Basics Right

Python Crash Course on Basics

Python for Data Science - Crash Course

MP Neuron Model

MP Neuron in Python

Summary of MP Neuron

Perceptron

Perceptron in Python

Sigmoid Neuron

Sigmoid Neuron Implement with Python

Basic Probability

Deep Neural Networks

Universal Approximation Theorem

Deep Learning with TensorFlow 2.x

Activation Functions in Deep Learning Neural Networks

Applying Deep Learning