Python Machine Learning: A Practical Beginner's Guide to Understanding Machine Learning, Deep Learning and Neural Networks with Python, Scikit-Learn, Tensorflow and Keras
... book, you can build your very own machine learning model or neural network ... always look for some parts of the code on the Internet. You should remember that ... about. You can always use machine learning to automate processes at work ...
This book also introduces neural networks with TensorFlow, runs through the main applications (regression, ConvNets (CNNs), GANs, RNNs, NLP), covers two working example apps, and then dives into TF in production, TF mobile, and using ...
Python Machine Learning For Beginners: Handbook For Machine Learning, Deep Learning And Neural Networks Using Python, Scikit-Learn And TensorFlow
... dummies rather than the (k-1). For example, you could have a categorical variable that is known as Department, and inside this, there are going to be five categories or levels that are unique. Because of this, each of the dummy ...
Data Analytics: 7 Manuscripts – Data Analytics for Beginners, Deep Learning with Keras, Analyzing Data with Power BI, Reinforcement Learning with Python, Artificial Intelligence Python, Text Analytics with Python, Convolutional Neural Networks in Python
Book 1: Data Analytics For Beginners In this book you will learn: What is Data Analytics Types of Data Analytics Evolution of Data Analytics Big Data Defined Data Mining Data Visualization Cluster Analysis And of course much more!
Hands-On Deep Learning Architectures with Python: Create deep neural networks to solve computational problems using TensorFlow and Keras
... You. Only. Look. Once. (YOLO). The object detection architectures we've discussed ... real time. To counter these challenges, a new prediction-based (regression ... Unified,. Image sourced from the paper, You Only Look Once: Unified, Real-Time ...
Ultimate Neural Network Programming with Python: Create Powerful Modern AI Systems by Harnessing Neural Networks with Python, Keras, and TensorFlow (English Edition)
... Vishal Rajput. tweaks can be explored, such as incorporating new layer types or implementing more intricate layer connections. Additionally, options like extending the number of training epochs or altering the activation function can be ...
Python Deep Learning: Exploring deep learning techniques and neural network architectures with PyTorch, Keras, and TensorFlow
This second edition of Python Deep Learning will get you up to speed with deep learning, deep neural networks, and how to train them with high-performance algorithms and popular Python frameworks.
Advanced Deep Learning with TensorFlow 2 and Keras: Apply DL, GANs, VAEs, deep RL, unsupervised learning, object detection and segmentation, and more, 2nd Edition
Revised for TensorFlow 2.x, this edition introduces you to the practical side of deep learning with new chapters on unsupervised learning using mutual information, object detection (SSD), and semantic segmentation (FCN and PSPNet), further ...
Mastering TensorFlow 1.x: Advanced machine learning and deep learning concepts using TensorFlow 1.x and Keras
TensorFlow represents the data as tensors and the computation as graphs. This book is a comprehensive guide that lets you explore the advanced features of TensorFlow 1.x.
TensorFlow Machine Learning: Advanced Guide to Learn Machine Learning With Scikit-Learn, Keras and TensorFlow
Python Programming, Deep Learning: 3 Books in 1: A Complete Guide for Beginners, Python Coding for Ai, Neural Networks, & Machine Learning, Data Science/Analysis with Practical Exercises for Learners
3 Books in 1: A Complete Guide for Beginners, Python Coding for Ai, Neural ... Linux" distros (i.e. red hat enterprise and also centOS). It's possible to ... Arch Linux Arch Linux is quite competitive about maintaining using Python ...
PYTHON: the PYTHON PROGRAMMING for Beginners - the Easiest Crash Course to Learn the Python Basics!: (Python, Python Programming, Python for Dummies, Python for Beginners)
Everything that you must know in order to become productive in your line of work is in this book. Examples provided in this book are specific and relevant that you may encounter them in the ordinary course of performing your jobs.
Python: PYTHON TUTORIAL - Learn the Basics of Python Programming in 7 DAYS Or LESS!: (Python, Python Programming, Python for Dummies, Python for Beginners, Python Crash Course)
What you will learn Build machine learning models particularly focused on the MNIST digits Work with Docker and Keras to build an image classifier Understand natural language models to process text and images Prepare your dataset for ...
Hands-On Convolutional Neural Networks with TensorFlow: Solve computer vision problems with modeling in TensorFlow and Python
This book is an introduction to CNNs through solving real-world problems in deep learning while teaching you their implementation in popular Python library - TensorFlow. By the end of the book, you will be training CNNs in no time!
Keras 2.x Projects: 9 projects demonstrating faster experimentation of neural network and deep learning applications using Keras
... words to use: MaxWords = 10000 Let's create the Tokenizer: Tok = Tokenizer(num_words=MaxWords) Finally, we can perform the tokenization operation: XTrain = Tok.sequences_to_matrix(XTrain, mode='binary') XTest = Tok.sequences_to_matrix ...
Hands-On Transfer Learning with Python: Implement advanced deep learning and neural network models using TensorFlow and Keras
What you will learn Set up your own DL environment with graphics processing unit (GPU) and Cloud support Delve into transfer learning principles with ML and DL models Explore various DL architectures, including CNN, LSTM, and capsule ...
Deep Learning With Python: Develop Deep Learning Models on Theano and TensorFlow Using Keras
Develop Deep Learning Models on Theano and TensorFlow Using Keras Jason Brownlee. 6.2. Pima. Indians. Onset. of. Diabetes. Dataset. In this tutorial we are going to ... Pima Indians Onset of Diabetes Dataset 29 Pima Indians Onset of Diabetes ...
Hands-On Computer Vision with TensorFlow 2: Leverage deep learning to create powerful image processing apps with TensorFlow 2.0 and Keras
This book will help you explore TensorFlow 2, the brand new version of Google's open source framework for machine learning. You will understand how to benefit from using convolutional neural networks (CNNs) for visual tasks.
Artificial Neural Networks and Machine Learning – ICANN 2019: Theoretical Neural Computation: 28th International Conference on Artificial Neural Networks, Munich, Germany, September 17–19, 2019, Proceedings, Part I
... probability of the entity's existence and orientation represents properties ... theory of neural networks and a new direction in the field of deep learning. The ... 10 [4]. Using the single CapsNet model same as [3], Xi et al. [5] reached ...
Machine Learning with Python: A Step by Step Guide for Absolute Beginners to Program Artificial Intelligence with Python. Neural Networks and Data Science from Pre-Processing to Deep Learning
Have you been hearing about some of the buzzwords in the world of business like data science, data analysis, and machine learning, but worry that this is going to be too hard for you to catch onto and learn more about?
Deep Learning for Computer Vision: Expert techniques to train advanced neural networks using TensorFlow and Keras
... wiki/ Errors_and_residuals) or deviations (https://en.wikipedia. org/wiki/Deviation_(statistics)). From a statistical point of view, this is a measure of the quality of an estimator (it is always nonnegative, and values closer to zero ...
Intelligent Projects Using Python: 9 real-world AI projects leveraging machine learning and deep learning with TensorFlow and Keras
Implement machine learning and deep learning methodologies to build smart, cognitive AI projects using Python Key FeaturesA go-to guide to help you master AI algorithms and concepts8 real-world projects tackling different challenges in ...
Hands-On Guide To IMAGE CLASSIFICATION Using Scikit-Learn, Keras, And TensorFlow with PYTHON GUI
... Programming for Animation and Games; C # Programming for SMA / SMK and Students; MATLAB For Students and Researchers; Graphics in JavaScript: Quick Learning Series; JavaScript Image Processing Methods: From A to Z; Java GUI Case Study ...
This website uses cookies and collects data for optimal performance. Your continued use signifies agreement to our Privacy Policy.
