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4 Best Deep Learning Python Courses & Tutorials of 2020

Deep Learning Python Courses

With so many Deep Learning Python courses, students find it extremely difficult to meet their needs. Learners often ask if there is an Deep Learning Python course for each case. The response is YES. Below are popular courses available. Registering for the right course is an important factor in your career progression. In this article, the best Deep Learning Python courses were selected by experts in 2020.

The main aim is to illustrate the best known courses in every category.

Select one that best suits your needs, based on your preference.

However, let’s look at the best Deep Learning Python courses on the market.

1. Data Science: Natural Language Processing (NLP) in Python

Duration: 2-3 hours

Rating: 4.5 out of 5

It is aimed at providing a better understanding of Natural Language Processing (NLP) Deep Learning modules, to learn how deep neural networks can be built by enhancing and increasing the number of training layers per network. You will start by acquiring a basic understanding of calculus, and then move on to understand backpropagation and its implementation for deep learning training in neural networks. The course has been designed by Lazy Programmer Inc. who worked for more than five years with Kernel Machines and Deep Learning. He will help you understand a few of the advanced Deep Learning to Construct Natural Language Processing (NLP) in Python techniques during the course.

Key Highlights:

  • Learn how to show Theano ‘s dominant mechanism of seamless CPU and GPU use, and how to apply convolutionary neural networks to image analysis
  • An introductory course required to better understand Deep Learning and Neural Networks using Python
  • Be confident in the implementation of Deep Learning in your current work and in further research after the course has been completed
  • Learn regarding recurrent neural networks and develop the theory that focuses on supervised learning and integrates search, image recognition, and object processing into your product offerings

You can Sign up Here

2. Introduction to Deep Learning in Python (DataCamp)

Duration: 4 hours

Rating: 4.5 out of 5

If you are keen to learn the fundamentals of Neural Networks and developing Deep Learning modules with Keras 2.0 then this DataCamp course is the right option for you. Taking this class will offer you a brief overview to Deep Learning which provides the most incredible abilities in different areas such as natural language processing, artificial intelligence , robotics, and image recognition. This tutorial consists of four separate chapters, among which is completely free to enroll in the first chapter, “Basics of Deep Learning and Neural Networks” During the course, with Keras 2.0, the newest iteration of a cutting-edge library for deep learning in Python, you can gain hands-on, practical knowledge of how to use deep learning.

Key Highlights:

  • Understand how to construct deep learning models for both classification and regression using the Keras library
  • Understand the basic concepts and terminology of deep learning, and understand how deep learning techniques are so strong
  • Know how to develop neural network forecasts by using the ‘Backward Propagation’ method;
  • Get constant support from experienced professionals to answer your Deep Learning and Python-related queries
  • Know the Specify-Compile-Fit workflow used to make precise forecasts

You can Sign up Here

3. Machine Learning with Python: From Linear Models to Deep Learning (edX)

Duration: Self-paced

Rating: 4.5 out of 5

It is one of Deep Learning ‘s best courses to help you understand about the concepts and algorithms to transform training data into convincing automated predictions. You will cover a variety of topics throughout the course, such as Representation, Overfitting, Regularization, Generalization, VC Dimension and many more. This class is part of the MITx MicroMaster in Data Science program, which means you can move on to learn some other advanced python data science concepts after completing this course. Completing the course will give you a completion certificate which can be shared with your resume or LinkedIn profile to show your skills.

Key Highlights:

  • Learn how various models such as linear models, kernel machines, neural networks and graphical models can be implemented and analyzed
  • Get a basic understanding of the principles behind the problems of machine learning, such as classification, regression, clustering and reinforcement learning
  • Get guidance and support from a team of professional teachers to help you understand the topics with hands-on projects and activities more clearly
  • Including numerous video tutorials, quizzes and useful learning material to help you more clearly understand the topics
  • Understand how machine learning projects can be implemented and organised, from training, validation, parameter tuning to feature engineering

You can Sign up Here

4. Data Science: Deep Learning in Python (Udemy)

Duration: 10-11 hours

Rating: 4.6 out of 5

This course will help you understand about using basic deep learning techniques to create your first artificial neural network. With the assistance of Python and NumPy, you can start with the basic building block to construct full-on non-linear neural networks and then move on to learning the most important method of training-backpropagation. The course is developed by Lazy Programmer Inc. professional teachers, who will include realistic examples during the course to help you understand how insightful thinking can be applied to something. You can also move toward learning some of the best deep learning training & tutorials after completing the course.

Key Highlights:

  • Learn about the different types of neural networks and the different types of problems that these neural networks can solve
  • An advanced course that focuses with the help of Python and NumPy on ‘how to build and understand’ deep neural networks
  • Learn how deep learning actually operates, how to code a Python, NumPy and Google TensorFlow neural network from scratch
  • Absolutely free to register from your comfort zone with the freedom to study
  • Know the different terms of the neural networks such as Activation, Backpropagation and Feedforward

You can Sign up Here

Wrapping Up

This is the list of the 4 Best Deep Learning Python Courses & Tutorials of 2020. They are popular and loved by many experienced Deep Learning learners. You will find between these courses what you need to learn in order to continue your Deep Learning journey.

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