Give as a gift or purchase for a team or group. Learn data analysis and machine learning and how python relates to each. I am going to paste a snippet that you should use to replace the code with, should you be hitting an error: It's going to be very likely your accuracy out of sample is a bit worse, same with loss. This is more of a deep learning quick start! If you're familiar with Keras previously, you can still use it, but now you can use tensorflow.keras to call it. Probability and Statistics for Deep Learning. Now let's build our model! Next, we have our loss metric. Each successive layer uses the … deeplearning.ai is also partnering with the NVIDIA Deep Learning Institute (DLI) in Course 5, Sequence Models, to provide a programming assignment on Machine Translation with deep learning. Language (Python Programming Deep Learning). A hidden layer is just in between your input and output layers. We're going to go with the simplest neural network layer, which is just a Dense layer. There's even some examples to be shown. The activation function is meant to simulate a neuron firing or not. It's going to take the data we throw at it, and just flatten it for us. C++ C++ is unlikely to be your first choice when developing an AI application, but when you need to … Used by thousands of students and professionals from top tech companies and research institutions. (Investing Book 1). After your input layer, you will have some number of what are called "hidden" layers. Hi, I'm an expert in Python programming, Machine Learning, Deep Learning, Natural Language Processing, Data Mining and Image Processing. JupyterLab is a web-based interactive development environment for Jupyter notebooks, code, and data. These promotions will be applied to this item: Some promotions may be combined; others are not eligible to be combined with other offers. Starter Vegetable Gardens: A Practical Guide to Grow Your Vegetables and Fruit. A Guide to Master Python, Data Science and Analysis. Reviewed in the United States on June 14, 2020. But, for now, woo! Welcome everyone to an updated deep learning with Python and Tensorflow tutorial mini-series. My goal was to create a chatbot that could talk to people on the Twitch Stream in real-time, and not sound like a total idiot. Over 1 million titles. Advanced Methods to Learn How to Create Codes with This Machine Learning Tool. So every time you want to run an algorithm on a data set, all you have to do is install and load the necessary packages with a single command. If you want to design a game then Python computer programming language would help you to do that. So it's going to send it's 0 or a 1 signal, multiplied by the weights, to the next neuron, and this is the process for all neurons and all layers. Then you can start reading Kindle books on your smartphone, tablet, or computer - no Kindle device required. I think the best part of this book is the code and practical exercises that will help you master the programming. Deep Learning Applications. This book is explains the language so that anyone can understand and learn it. KETO SLOW COOKER COOKBOOK: Keto Diet And How The Slow Cooker Can Help You Achieve Your Goals. In this case, our activation function is a softmax function, since we're really actually looking for something more like a probability distribution of which of the possible prediction options this thing we're passing features through of is. It just means things are going to go in direct order. Remember why we picked relu as an activation function? This is what they are talking about in those videos and this is what I tried to implement just now”. Explore and discover an in depth look into the basics of Coding in 6 Programming Languages and be on your way to becoming a programming wizard. The testing variants of these variables is the "out of sample" examples that we will use. You are getting 3 books in 1. Unable to add item to List. Basic Knots Tutorial and Techniques, Credit Repair: A Guide For Both Beginners And Experts: Smart And Practical Secrets To Quickly Raise Your Credit Card Score And Improve Your Money Management Like A Pro, Keto Chaffle Recipes: The Ultimate Cookbook with 101 Easy Recipes which will teach you How to prepare Delicious Ketogenic Waffles for your Low Carb and Gluten-Free Diet. If you have further questions too, you can join our Python Discord. Grow More Using Less Space! No going backwards...for now. Deep Learning WizardPython. Programming is a superpower. It could be very useful for someone needing to learn a deeper level of python. Deep Learning With Python: Creating a Deep Neural Network. If you like interactive learning, this is the best online resource to … There is a LOT of information here and that might go over some people's heads, but if you are dedicated and really wanting to learn Python, this book can help. Let’s continue this article and see how can create our own Neural Network from Scratch, where we will create an Input Layer, Hidden Layers and Output Layer. In order to navigate out of this carousel please use your heading shortcut key to navigate to the next or previous heading. This is our final layer. I actually had to look up the author to make sure he was a native English speaker. The y_train is the label (is it a 0,1,2,3,4,5,6,7,8 or a 9?). Python for BEGINNERS with Hands-on Fun Project & Ga... Python Tricks: A Buffet of Awesome Python Features. Hone your Python Programming skills and gain a sharp edge over other programmers the EASIEST way possible... with this practical beginner’s guide! Python is an interpreted, high-level, general-purpose programming language that emphasizes code readability with its notable use of significant whitespace. As data travels through this artificial mesh, each layer processes an aspect of the data, filters outliers, spots familiar entities, and produces the final output. Please try again. Now that's loss and accuracy for in-sample data. This brief tutorial introduces Python and its libraries like Numpy, Scipy, Pandas, Matplotlib; frameworks like Theano, TensorFlow, Keras. Hello and welcome to a deep learning with Python and Pytorch tutorial series. It's generally a good idea to "normalize" your data. Let's add another identical layer for good measure. Grow Vegetables, Fruits, and Herbs with Your Scientific System, Cast Iron Cookbook: The Ultimate Cast Iron Cookbook with more then 200 Delicious Recipes for your Healthy and Easy Meal at Home, Stock Market Investing: A Comprehensive Guide for Beginners: Master the Financial Markets and Start Making Profit - 2 Manuscripts: Stock Trading Strategy, Dividend Investing. I can explain you everything and I have an experience in machine learning. Reviewed in the United Kingdom on May 23, 2020. This typically involves scaling the data to be between 0 and 1, or maybe -1 and positive 1. Neural networks are exceptionally good at fitting to data, so much so that they will commonly over-fit the data. It attempts to minimize loss. My recent projects are "Sh More. Again, there are many choices, but some form of categorical crossentropy is a good start for a classification task like this. It's 28x28 images of these hand-written digits. Boom, you've got a deep neural network! This is an interesting book. # evaluate the out of sample data with model. Just getting into this book, It reads as though it were written by someone who speaks English as a second language, or if it were translated from another language. It's a multi-dimensional array. Your recently viewed items and featured recommendations, Select the department you want to search in. Reviewed in the United States on September 14, 2020. This shopping feature will continue to load items when the Enter key is pressed. There was a problem loading your book clubs. The main programming language we are going to use is called Python, which is the most common programming language used by Deep Learning practitioners. The best part of the book is that there are practical quizzes to check your Python knowledge and programming skills. It's nowhere near as complicated to get started, nor do you need to know as much to be successful with deep learning. 35 % started a new career after completing these courses. Python is an easy-to-learn programming language, it is especially good for beginners. Getting a high accuracy and low loss might mean your model learned how to classify digits in general (it generalized)...or it simply memorized every single example you showed it (it overfit). This is where we pass the settings for actually optimizing/training the model we've defined. I think if I were more interested in the subject this would have been a better read for me so for that reason I recommend you have a genuine interested in learning python programming before picking up this book. 10 units for 10 classes. Since doing the first deep learning with TensorFlow course a little over 2 years ago, much has changed. Anthony took it upon himself to change that and. The mathematical challenge for the artificial neural network is to best optimize thousands or millions or whatever number of weights you have, so that your output layer results in what you were hoping for. Reviewed in the United States on November 28, 2020. Take a lot of notes. Keras has become so popular, that it is now a superset, included with TensorFlow releases now! Easily Boost Your Skills In Python Programming & Become A Master In Deep Learning & Data Analysis! How about the value for y_train with the same index? JupyterLab is flexible: configure and arrange the user interface to support a wide range of workflows in data science, scientific computing, and machine learning. Have a blast learning the Android SDK and user interface design for Android devices with this hilarious, irreverent and easy-to-read guide! Unlimited reading. A neural network doesn't actually attempt to maximize accuracy. Mental Toughness: The 21-Step Program to Build a Successful Mindset, Boost Your Resilience and Reach Your Goals, Aquaponics for Beginners: Tips and Techinques to a Successful Aquaponic Garden at Home. So, we need to take this 28x28 image, and make it a flat 1x784. Reviewed in the United States on August 15, 2020. Artificial Neural Network Backpropagation Python Programming Deep Learning. You've subscribed to Python Programming Deep Learning! For details, please see the Terms & Conditions associated with these promotions. A tensor in this case is nothing fancy. Solving for this problem, and building out the layers of our neural network model is exactly what TensorFlow is for. A feed forward model. Practical Machine Learning with Python Learn theory, real world application, and the inner workings of regression, classification, clustering, and deep learning. Instead, our system considers things like how recent a review is and if the reviewer bought the item on Amazon. Do you believe that this item violates a copyright? Thrive in the IT industry with this comprehensive Python Programming crash course! If you like Easy to understand books with best practices from experienced programmers then you’ll love Dominique Sage’s Learn Python book series. Want to start coding in Python but have no idea where to start? Well, if you just have a single hidden layer, the model is going to only learn linear relationships. LEARN Python: From Kids & Beginners Up to Expert Coding - 2 Books in 1 - (Learn Cod... Coding Languages for Absolute Beginners: 6 Books in 1- Arduino, C++, C#, Powershell... Anthony Adams is a computer programmer and author who was born and raised in London but moved to the United States when he was in his mid-twenties, to follow his dreams. While some of this book went over my head, I can appreciate the amount of information these books provide to someone who is interested in becoming a python programming master. We are going to use the MNIST data-set. Some visual recognition datasets have set benchmarks for supervised learning (Caltech101, Caltech256, CaltechBirds, CIFAR-10 andCIFAR-100) and … A simple example would be a stepper function, where, at some point, the threshold is crossed, and the neuron fires a 1, else a 0. The next tutorial: Loading in your own data - Deep Learning basics with Python, TensorFlow and Keras p.2, Introduction to Deep Learning - Deep Learning basics with Python, TensorFlow and Keras p.1, Loading in your own data - Deep Learning basics with Python, TensorFlow and Keras p.2, Convolutional Neural Networks - Deep Learning basics with Python, TensorFlow and Keras p.3, Analyzing Models with TensorBoard - Deep Learning basics with Python, TensorFlow and Keras p.4, Optimizing Models with TensorBoard - Deep Learning basics with Python, TensorFlow and Keras p.5, How to use your trained model - Deep Learning basics with Python, TensorFlow and Keras p.6, Recurrent Neural Networks - Deep Learning basics with Python, TensorFlow and Keras p.7, Creating a Cryptocurrency-predicting finance recurrent neural network - Deep Learning basics with Python, TensorFlow and Keras p.8, Normalizing and creating sequences for our cryptocurrency predicting RNN - Deep Learning basics with Python, TensorFlow and Keras p.9, Balancing Recurrent Neural Network sequence data for our crypto predicting RNN - Deep Learning basics with Python, TensorFlow and Keras p.10, Cryptocurrency-predicting RNN Model - Deep Learning basics with Python, TensorFlow and Keras p.11, # deep learning library. While this book starts saying it's designed for beginners, it can be hard to follow at times. You can figure out your version: Once we've got tensorflow imported, we can then begin to prepare our data, model it, and then train it. Skip to content. We can get the actual number pretty simply: There's your prediction, let's look at the input: Awesome! Like internet search dumped into a book. # how will we calculate our "error." Okay, I think that covers all of the "quick start" types of things with Keras. To get the free app, enter your mobile phone number. The text is filled with rambling bad grammar and confusing wording. Python is an interpreted, high-level, general-purpose programming language that emphasizes code readability with its notable use of significant white space. 1 node per possible number prediction. Find all the books, read about the author, and more. Practice Lab | 8h. Deep Learning can be used for making predictions, which you may be familiar with from other Machine Learning algorithms. Python is an interpreted, high-level, general-purpose programming language that emphasizes code readability with its notable use of significant whitespace. This means that, while Deep Learning with PyTorch provides much cleaner code than many other books, it also requires readers to have a solid foundation in Python to fully understand the samples. There was an error retrieving your Wish Lists. Earn a … Let's say that neuron is in the first hidden layer, and it's going to communicate with the next hidden layer. Easily boost your skills in Python programming and become a master in deep learning and data analysis! About the Book Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. It also analyzes reviews to verify trustworthiness. If you're interested in more of the details with how TensorFlow works, you can still check out the previous tutorials, as they go over the more raw TensorFlow. The Beginner's Guide to Raising Chickens: Keeping Chickens Happy and Healthy, Building Pretty Chicken Coops And Cooking With Your Fresh Eggs And Meat. Now, we'll pop in layers. Bring your club to Amazon Book Clubs, start a new book club and invite your friends to join, or find a club that’s right for you for free. Redemption links and eBooks cannot be resold. What exactly do we have here? Great, our model is done. I've more than Three years experience in this field. It was flat. A basic neural network consists of an input layer, which is just your data, in numerical form. Following the release of deep learning libraries, higher-level API-like libraries came out, which sit on top of the deep learning libraries, like TensorFlow, which make building, testing, and tweaking models even more simple. You can do way more than just classifying data.. Related Course: Deep Learning with Python. One hidden layer means you just have a neural network. A sequential model is what you're going to use most of the time. SoloLearn Python 3 course (FREE) 3. The activation function is relu, short for rectified linear. Reviewed in the United States on November 30, 2020. Deep learning consists of artificial neural networks that are modelled on similar networks present in the human brain. Neural network aims to minimize loss. It's just a great default to start with. Macramé for Beginners: An Essential Guide for Beginners with Easy Macramé Illustrated Patterns to Make Your Homemade Projects. LEARN Python: UP to EXPERT CODING. This will serve as our input layer. Does this book contain inappropriate content? Below are some resources that I used to study deep learning: Python programming 1. Reviewed in the United States on November 26, 2020. As we train, we can see loss goes down (yay), and accuracy improves quite quickly to 98-99% (double yay!). As a beginner, you might feel a bit intimidated by the complexities of coding. Update your device or payment method, cancel individual pre-orders or your subscription at. By the time you read the maths of deep learning, you will feel “Oooo.. Enjoy all the deep learning. LAB: Deep Learning Programming with Python. Learner Career Outcomes. Just like Linear Algebra, ‘Statistics and Probability’ is its … If you want to create a dynamic website with PHP and MySQL, then you will love Sergey Skudaev's PHP Programming for Beginners. In his 3-in-1 Python crash course for beginners, Anthony Adams gives novices like you simple, yet efficient tips and tricks to become a MASTER in Python coding for artificial intelligence, neural networks, machine learning, and data science/analysis! Behind this progress is deep learning—a combination of engineering advances, best practices, and theory that enables a wealth of previously impossible smart applications. The book also makes use of Python’s object-oriented programming features to extend PyTorch’s functionality. Avoid. By that same token, if you find example code that uses Keras, you can use with the TensorFlow version of Keras too. So the x_train data is the "features." These ebooks can only be redeemed by recipients in the US. At the time of this writing (March 2016), Google’s AlghaGo program just beat 9-dan professional Go player Lee Sedol at the game of Go, a … Python - Deep Learning Wizard. To begin, we need to find some balance between treating neural networks like a total black box, and understanding every single detail with them. Does this book contain quality or formatting issues? One of the Top-5 programming languages. THE PROGRAMMING BIBLE; Is an Unfair Advantage to take your Tech Skills to the Next Level what you're looking for? Discover the Effectiveness of Growing Your Garden by Using the Raised Bed Technique. The first step is to download Anaconda, which you can think of as a platform for you to use Python “out of the box”. Python is a general-purpose high level programming language that is widely used in data science and for producing deep learning algorithms. Perform DL programming tasks with Python, such as performing series expansion and calculus, and work with Tensorflow and scikit-image. In this case, the features are pixel values of the 28x28 images of these digits 0-9. Tensors are just multi-dimensional arrays, # mnist is a dataset of 28x28 images of handwritten digits and their labels, # unpacks images to x_train/x_test and labels to y_train/y_test, # a simple fully-connected layer, 128 units, relu activation, # our output layer. Discover Python’s best practices and the power of beautiful & Pythonic code with simple examples and a step-by-step narrative. Deep Learning. Written by Keras creator and Google AI researcher François Chollet, this book builds your … Please try again. Additional gift options are available when buying one eBook at a time. It's been a while since I last did a full coverage of deep learning on a lower level, and quite a few things have changed both in the field and regarding my understanding of deep learning. There is a LOT of information in this book. Prebuilt Libraries: Python has 100s of pre-built libraries to implement various Machine Learning and Deep Learning algorithms. Burn Fat and Start Losing Weight with 16 Weeks Sirt Meal Plan, DAY TRADING STRATEGIES - THE BEGINNER’S GUIDE FOR 2020: HOW TO DEVELOP THE RIGHT MONEY MANAGEMENT MINDSET TO GENERATE A PASSIVE INCOME AND DAY TRADE FOR A LIVING. Easily boost your skills in Python programming and become a master in deep learning and data analysis! He attended Imperial College London where he attained his degree in computing and followed this with a second course at King's College, also in London. Not quite 0 to 1. PHP Programming for Beginners: Key Programming Concepts. This layer has 128 units. Becoming good at Deep Learning opens up new opportunities and gives you a big competitive advantage. Okay, that makes sense. Practice the coding at home. Let's take a quick peak. Deep learning consists of artificial neural networks that are modeled on similar networks present in the human brain. Computer programming languages: 2 books in 1: For beginners or intermediate. One such library that has easily become the most popular is Keras. $30 USD in 1 day (7 Reviews) 3.1. muhaamadmaaz. Please try again. It's nowhere near as complicated to get started, nor do you need to know as much to be successful with deep learning. Currently, relu is the activation function you should just default to. Same thing is true for the Adam optimizer. An updated deep learning introduction using Python, TensorFlow, and Keras. These are examples from our data that we're going to set aside, reserving them for testing the model. For the sake of simplicity, we'll be using the most common "hello world" example for deep learning, which is the mnist dataset. This item has a maximum order quantity limit. After viewing product detail pages, look here to find an easy way to navigate back to pages you are interested in. Since doing the first deep learning with TensorFlow course a little over 2 years ago, much has changed. Codecademy Python 2 course (FREE) 2. Learn more. Easy Keto Cookbook for Beginners: 100 Quick & Easy, Low-Carb, High-Fat Recipes. Running on the GPU - Deep Learning and Neural Networks with Python and Pytorch p.7 Go Basic Network Analysis and Visualizations - Deep Learning and Neural Networks with Python and Pytorch p.8 Welcome everyone to an updated deep learning with Python and Tensorflow tutorial mini-series. TensorFlow is used for all things "operations on tensors." Softmax for probability distribution. Also check out the Machine Learning and Learn Machine Learning subreddits to stay up to date on news and information surrounding deep learning. The world of data learning, collecting, mining, sorting, processing and cleaning up, is all in here. Book is VERY large print, so much is wasted space. This is just barely scratching the surface of what's available to you, so start poking around Tensorflow and Keras documentation. In our case, each "pixel" is a feature, and each feature currently ranges from 0 to 255. Learn deep learning and deep reinforcement learning math and code easily and quickly. The tutorial explains how the different libraries and frameworks can be applied to solve complex real world problems. Deep Learning Deep learning is making waves. Let's change that with a handy utility function: Alright, still a 5. There’s a lot to learn. Chess for Kids and Beginners: The complete Chess book for Kids and Beginners Player... To calculate the overall star rating and percentage breakdown by star, we don’t use a simple average. Learn Python 2 on Codecademy. This refers to the fact that it's a densely-connected layer, meaning it's "fully connected," where each node connects to each prior and subsequent node. Including 250 Easy-To-Prepare Delicious Recipes, From Breakfast To Dinner, Optavia Air Fryer Cookbook 2021: The Complete Optavia Air Fryier Cookbook; 500+ Lean & Green, Delicious and Effortless Recipes to Kill your Hunger and Boost your Energy for a Long-Term Transformation, Learn Python: This Book Includes: Crash Course and Coding. A must have for anyone who programs in python. You need practical experience to be a professional programmer. Guide to Visual Recognition Datasets for Deep Learning with Python Code analyticsindiamag.com - Jayita Bhattacharyya. LEARN Python: KIDS & BEGINNERS. Why is this? What it is, how to install it and practice programs to teach you. Don't waste your money. Additional gift options are available when buying one eBook at a time. Finally, with your model, you can save it super easily: That sure doesn't start off as helpful, but recall these are probability distributions. So this is really where the magic happens. The Ultimate Guide To Everything You Must Know, With Sample Letters To Defend Your Rights. Python Machine Learning: A Beginner’s Guide to Python Programming for Machine Learning and Deep Learning, Data Analysis, Algorithms and Data Science With Scikit Learn, TensorFlow, PyTorch and Keras Paperback – October 21, 2019 Now we need to "compile" the model. Full code up to this point, with some notes: As of Dec 21st 2018, there's a known issue with the code. After needing to reread a few sections, it started to make more sense. In his spare time, Anthony likes to take himself off into the mountains to camp, fish and hike. Badly written, badly formatted & editing is non-existent. Study the transmissions and learn from the different variations. Add the fact that most Python Programming crash course guides make learning harder than it has to be! It has 10 nodes. The idea is a single neuron is just sum of all of the inputs x weights, fed through some sort of activation function. 11 % got a pay increase or promotion Shareable Certificate. Learn to find the errors in the coding and the scripts. Deep learning is a class of machine learning algorithms that use several layers of nonlinear processing units for feature extraction and transformation. But it was around this time that he suddenly realized that the books he was reading as part of his work, while clear to him, would not be clear to the ordinary person on the street. In fact, you can just do something like: For this tutorial, I am going to be using TensorFlow version 1.10. Just like our image. In fact, it should be a red flag if it's identical, or better. 35 % got a tangible career benefit from this course. Next, we want our hidden layers. Was the input layer flat, or was it multi-dimensional? He is passionate about his classic Norton motorcycle and takes it on long rides at weekends, stopping off at the secluded beaches and campsites he finds wherever possible. Previous page of related Sponsored Products. This is a good reference book for any online or college course. This step-by-step guide will have you creating programs from scratch in no time! Python is an interpreted, high-level, general-purpose programming language that emphasizes code readability with its notable use of significant white space. EMPATH: Three steps to achieve happiness: healing, awakening and empowerment with a life strategy for sensitive people. Our real hope is that the neural network doesn't just memorize our data and that it instead "generalizes" and learns the actual problem and patterns associated with it. What do you want to achieve through the language? THE NATIVE AMERICAN HERBALISM ENCYCLOPEDIA : A Pocket Guide to Finding Medical Herbs,Creating Herbal Remedies,and Discovering the Secrets of Native Herbology of North America to Heal Common Ailments. There's a problem loading this menu right now. You begin at the beginning by learning the basics. There are many ways for us to do this, but keras has a Flatten layer built just for us, so we'll use that. Upon moving to the USA, Anthony took a job in Los Angeles and quickly found that the Californian lifestyle suited him. Two or more hidden layers? It's a dataset of hand-written digits, 0 through 9. Loss is a calculation of error. We will show an example of using outside data as well, but, for now, let's load in this data: When you're working with your own collected data, chances are, it wont be packaged up so nicely, and you'll spend a bit more time and effort on this step. Enter your mobile number or email address below and we'll send you a link to download the free Kindle App. With the help of this 3-in-1 guide, you will be given carefully sequenced Python Programming lessons that’ll maximize your understanding, and equip you with all the skills for real-life application! As data travels through this artificial mesh, each layer processes an aspect of the data, filters outliers, spots familiar entities, and produces the final output. But this is NOT an easy read. Python can execute fragments on the fly..that’s why it’s so popular. Til next time. Recall our neural network image? If you have many hidden layers, you can begin to learn non-linear relationships between your input and output layers. In order to create a chatbot, or really do any machine learning task, of course, the first job you have is to acquire training data, then you need to structure and prepare it to be formatted in a "input" and "output" manner that a machine learning algorithm can digest. 609 Letter Template And Credit Repair Secrets: How To File A Credit Dispute And Increase Your Score. Now that we have successfully created a perceptron and trained it for an OR gate. Life changing books for anyone trapped in an unhealthy relationship. What makes Python so popular in the IT industry is that it uses an object-oriented approach, which enables programmers to write clear, logical code for all types of projects, whether big or small. The main thing is that you can write simple and effective programs with its help without spending a lot of time for them. Prime members enjoy FREE Delivery and exclusive access to music, movies, TV shows, original audio series, and Kindle books. This is why we need to test on out-of-sample data (data we didn't use to train the model). Sirtfood Diet: 4 Books in 1: The Complete Guide to Activate your "Skinny Gene" with 700+ Delicious, Quick & Easy Recipes. Top subscription boxes – right to your door, © 1996-2020, Amazon.com, Inc. or its affiliates. Ultimate Step by Step Guide to Machine Learning Using Python: Predictive modelling ... Python for Beginners: A Crash Course Guide to Learn Coding and Programming With Pyt... Python: Programming Basics for Absolute Beginners. You will have the opportunity to build a deep learning project with cutting-edge, industry-relevant content. There are many more to test for sure, but, if you don't know what to use, use relu to start.
2020 python programming deep learning