Deep learning and Machine Learning with Python

Deep learning and Machine Learning with Python, available at $19.99, has an average rating of 4.88, with 30 lectures, based on 42 reviews, and has 88 subscribers.

You will learn about Data visualization libraries such as Pandas, Matplotlib, Seaborn, and NumPy. Key concepts of machine learning, including supervised and unsupervised learning, and understand the differences between them. Implementation of linear regression models. Understanding the concept of cost functions. Employing gradient descent for optimization. Decision tree algorithms, including XGBoost and Random Forests. Understand how ensemble methods work and their applications in predictive modeling, enabling them to construct more accurate and robust models. They will also be able to extend their skills to logistic regression, including cost functions and gradient descent specific to classification problems. This course is ideal for individuals who are Beginner Python Developers enthusiastic about Learning Deep Learning and Data Science or Students who have at least high school knowledge in math and who want to start learning Machine Learning. or Any people who are not that comfortable with coding but who are interested in Deep Learning and want to apply it easily on datasets. or Any data analysts who want to level up in Deep Learning. or Anyone interested in Deep Learning. It is particularly useful for Beginner Python Developers enthusiastic about Learning Deep Learning and Data Science or Students who have at least high school knowledge in math and who want to start learning Machine Learning. or Any people who are not that comfortable with coding but who are interested in Deep Learning and want to apply it easily on datasets. or Any data analysts who want to level up in Deep Learning. or Anyone interested in Deep Learning.

Enroll now: Deep learning and Machine Learning with Python

Summary

Title: Deep learning and Machine Learning with Python

Price: $19.99

Average Rating: 4.88

Number of Lectures: 30

Number of Published Lectures: 30

Number of Curriculum Items: 30

Number of Published Curriculum Objects: 30

Original Price: $19.99

Quality Status: approved

Status: Live

What You Will Learn

Data visualization libraries such as Pandas, Matplotlib, Seaborn, and NumPy.
Key concepts of machine learning, including supervised and unsupervised learning, and understand the differences between them.
Implementation of linear regression models.
Understanding the concept of cost functions.
Employing gradient descent for optimization.
Decision tree algorithms, including XGBoost and Random Forests.
Understand how ensemble methods work and their applications in predictive modeling, enabling them to construct more accurate and robust models.
They will also be able to extend their skills to logistic regression, including cost functions and gradient descent specific to classification problems.

Who Should Attend

Beginner Python Developers enthusiastic about Learning Deep Learning and Data Science
Students who have at least high school knowledge in math and who want to start learning Machine Learning.
Any people who are not that comfortable with coding but who are interested in Deep Learning and want to apply it easily on datasets.
Any data analysts who want to level up in Deep Learning.
Anyone interested in Deep Learning.

Target Audiences

Beginner Python Developers enthusiastic about Learning Deep Learning and Data Science
Students who have at least high school knowledge in math and who want to start learning Machine Learning.
Any people who are not that comfortable with coding but who are interested in Deep Learning and want to apply it easily on datasets.
Any data analysts who want to level up in Deep Learning.
Anyone interested in Deep Learning.

Master Deep Learning with Python for AI Excellence

Course Description:

This meticulously crafted course is designed to empower you with comprehensive knowledge and practical skills to thrive in the world of artificial intelligence.

Immerse yourself in engaging lectures and hands-on lab sessions that cover fundamental concepts, cutting-edge methodologies, and real-world applications of deep learning. Gain expertise in essential Python libraries, machine learning algorithms, and advanced techniques, setting a solid foundation for your AI career.

Course Highlights:

In-Demand Skills: Acquire the highly sought-after skills demanded by today’s AI-centric job market, opening doors to data science, machine learning, and AI development roles.

Hands-On Learning: Learn by doing! Our interactive lab sessions ensure you gain practical experience, from data preprocessing to model evaluation, making you a proficient deep learning practitioner.

Comprehensive Curriculum: From foundational Python libraries like Pandas and NumPy to cutting-edge neural network architectures like CNNs and RNNs, this course covers it all. Explore linear regression, logistic regression, decision trees, clustering, anomaly detection, and more.

Expert Guidance: Our experienced instructors are committed to your success. Receive expert guidance, personalized feedback, and valuable insights to accelerate your learning journey.

Project-Based Learning: Strengthen your skills with real-world projects that showcase your deep learning capabilities, building a compelling portfolio.

Practical Applications: Understand how deep learning powers real-world applications, including image recognition, natural language processing, recommendation systems, and autonomous vehicles.

Who Should Enroll:

Aspiring Data Scientists: Start your journey into data science and AI with the skills and knowledge needed to excel.

Machine Learning Enthusiasts: Deepen your understanding of machine learning and take it to the next level with deep learning applications.

AI Developers: Enhance your proficiency in deep learning to stay ahead in this rapidly evolving field.

Whether you’re new to AI or an experienced professional, this course empowers you to harness the full potential of deep learning and Python, opening doors to limitless opportunities. Don’t miss this chance to shape your future in artificial intelligence.

Course Curriculum

Section 1: Introduction

Understand the significance of deep learning and its implications.

Get familiar with essential Integrated Development Environments (IDEs).

Section 2: Python Libraries

Master data manipulation with Pandas.

Explore numerical operations with NumPy.

Dive into scientific analysis using Scipy.

Create visually appealing graphics with Matplotlib.

Craft elegant visualizations with Seaborn.

Section 3: Introduction to Deep Learning

Uncover the fundamental principles of deep learning.

Grasp the pivotal role of neural networks.

Section 4: Supervised vs. Unsupervised Learning

Demystify supervised and unsupervised learning.

Section 5: Linear Regression

Master linear regression for prediction.

Section 6: Multiple Linear Regression

Predict multiple outcomes using advanced techniques.

Section 7: Logistic Regression

Equip computers with decision-making capabilities.

Section 8: Decision Trees

Explore decision trees and essential companions like Xgboost and Random Forest.

Section 9: Clustering

Organize data through clustering.

Section 10: Anomaly Detection

Identify anomalies in data.

Section 11: Collaborative and Content-Based Filtering

Deliver personalized recommendations.

Section 12: Reinforcement Learning

Immerse in dynamic reinforcement learning.

Section 13: Neural Networks

Delve into the core of AI with neural networks.

Section 14: TensorFlow

Master the acclaimed deep learning library.

Section 15: Keras

Build and train deep learning models with ease.

Section 16: PyTorch

Explore the dynamic and versatile deep-learning library.

Section 17: RNN and CNN

Unlock specialized architectures for sequential data and image processing.

Upon course completion, you’ll possess a profound understanding of deep learning, ready to tackle diverse AI and machine learning challenges using Python’s robust toolkit.

This course equips you to confidently step into the realm of AI mastery. Experience the magic of AI and command your computer to achieve remarkable feats!

Enroll now and unlock the magic of Deep Learning and Python!”

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction to Deep learning and Introduction to IDE

Chapter 2: Python Libraries

Lecture 1: Pandas

Lecture 2: Numpy

Lecture 3: Scipy

Lecture 4: Matplotlib

Lecture 5: Seaborn

Chapter 3: Introduction to Deep Learning

Lecture 1: Introduction to Deep Learning

Chapter 4: Super vised vs Unsupervised

Lecture 1: Supervised vs Unsupervised

Chapter 5: Linear Regression

Lecture 1: Introduction to Linear Regression

Lecture 2: Cost Function

Lecture 3: Gradient Descent

Lecture 4: Over Fitting

Lecture 5: Gradient Descent for Linear Regression

Lecture 6: Linear Regression (Lab Session)

Chapter 6: Multiple Linear Regression

Lecture 1: Multiple Linear Regression

Chapter 7: Logistic Regression

Lecture 1: Introduction to Logistic Regression

Lecture 2: Cost Function , Gradient Descent for Logistic Regression

Lecture 3: Logistic Regression (Lab Session)

Chapter 8: Decision Trees

Lecture 1: Introduction to Decision Trees

Lecture 2: Xgboost

Lecture 3: Randomforest

Chapter 9: Clustering

Lecture 1: Clustering

Chapter 10: Anomaly Detection

Lecture 1: Anomaly Detection

Chapter 11: Collaborative and Content Based Filtering

Lecture 1: Collaborative and Content Based Filtering

Chapter 12: Reinforcement Learning

Lecture 1: Reinforcement Learning

Chapter 13: Neural Networks

Lecture 1: Neural Networks

Chapter 14: TensorFlow

Lecture 1: TensorFlow

Chapter 15: Keras

Lecture 1: Keras

Chapter 16: Pytorch

Lecture 1: Pytorch

Chapter 17: RNNs and CNNs

Lecture 1: RNN and CNN

Instructors

Selfcode Academy
Powered by 1stMentor

Rating Distribution

1 stars: 0 votes
2 stars: 0 votes
3 stars: 1 votes
4 stars: 4 votes
5 stars: 37 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

Menu