🔥𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐌𝐢𝐜𝐫𝐨𝐬𝐞𝐫𝐯𝐢𝐜𝐞𝐬 𝐀𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭𝐮𝐫𝐞 𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠 : https://www.edureka.co/microse....rvices-architecture- (𝐔𝐬𝐞 𝐂𝐨𝐝𝐞: 𝐘𝐎𝐔𝐓𝐔𝐁𝐄𝟐𝟎)
This Edureka's video on Microservices Design Patterns talks about the top design patterns you can use to build applications. In this video, you will learn the following:
00:00:00 Introduction
00:01:29 Why do we need Design Patterns?
00:03:41 What are Design Patterns?
00:04:28 What are Microservices?
00:06:00 Principles behind Microservices
00:10:24 Microservices Design Patterns

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Got a question on the topic? Please share it in the comment section below and our experts will answer it for you.

Please write back to us at sales@edureka.co or call us at IND: 9606058406 / US: 18338555775 (toll-free) for more information.

In this tutorial, we will be building a Node.js API with MongoDB and Mongoose to track exercises. Our API will pass a series of tests, including creating a new user with a POST request to /api/users, getting a list of all users with a GET request to /api/users, adding exercises with a POST request to /api/users/:_id/exercises, and retrieving a full exercise log of any user with a GET request to /api/users/:_id/logs. Thanks for watching and have a great day!

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This Machine Learning tutorial will help you understand why Machine Learning came into the picture, what is Machine Learning, and the types of Machine Learning., Machine Learning algorithms with a detailed explanation on linear regression, decision tree & support vector machine, and at the end you will also see a use case implementation where we classify whether a recipe is of a cupcake or muffin using SVM algorithm.

Dataset Link - https://drive.google.com/drive..../folders/1W7kaFk2vUk

Machine Learning Tutorial Part - 2: https://www.youtube.com/watch?v=_Wkx_447zBM

00:00 - 00:45 Why Machine Learning?
00:45 - 04:52 What is Machine Learning?
04:52 - 11:34 Types of Machine Learning
11:34 - 16:41 Machine Learning Algorithms
16:41 - 25:43 Linear Regression
25:43 - 34:00 Decision Trees
34:00 - 36:02 Support Vector Machine
36:02 - 01:02:40 Use case: Classify whether a recipe is of a cupcake or a muffin using SVM

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What is Machine Learning?
Machine learning is a core sub-area of artificial intelligence; it enables computers to get into a mode of self-learning without being explicitly programmed. When exposed to new data, these computer programs learn, grow, change, and develop by themselves.

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In this video, learn how to build your own Small Language Model (SLM) from scratch using Python, PyTorch, and Hugging Face datasets. We’ll walk through every step — from data collection and preprocessing to tokenization, transformer architecture, and model training.

You’ll discover how a compact 10–15 million parameter model can still generate coherent and meaningful text, using concepts inspired by GPT models. This tutorial simplifies complex AI topics like embedding layers, attention mechanisms, loss computation, and next-token prediction — all explained clearly with working code examples.

🔹 Topics Covered:

What are Small Language Models (SLMs)?

Using the TinyStories dataset from Hugging Face

Tokenization with OpenAI’s tiktoken library

Creating .bin training files for efficient processing

Building a Transformer architecture step-by-step

Implementing GPT-like attention blocks

Training configuration and hyperparameter tuning

Generating text from your trained SLM

🎯 Perfect for AI researchers, ML engineers, and enthusiasts who want to understand how GPT-style models actually work under the hood — without requiring massive GPUs or billion-parameter setups.

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** Tensorflow Training: https://www.edureka.co/ai-deep....-learning-with-tenso **
This video on "Deep Learning with Python" will provide you with detailed and comprehensive knowledge of Deep Learning, How it came into emergence. The various subparts of Data Science, how they are related and How Deep Learning is revolutionalizing the world we live in. This Tutorial covers the following topics:

1:49 Introduction To AI, ML, and DL
2:19 What is Deep Learning
7:30 Applications of Deep Learning
13:27 Structure of Perceptron
16:31 Demo: Perceptron from scratch
23:52 What is a Neural Network ?
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(450+ Hrs || 9 Months || 20+ Projects & 100+ Case studies)

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---------------------------------------------------------------

How it Works?

1. This is 21 hrs of Online Live Instructor-led course. Weekend class: 7 sessions of 3 hours each.
2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course.
3. At the end of the training you will have to undergo a 2-hour LIVE Practical Exam based on which we will provide you a Grade and a Verifiable Certificate!

- - - - - - - - - - - - - -

About the Course
Edureka's Deep learning with Tensorflow course will help you to learn the basic concepts of TensorFlow, the main functions, operations and the execution pipeline. Starting with a simple “Hello Word” example, throughout the course you will be able to see how TensorFlow can be used in curve fitting, regression, classification and minimization of error functions. This concept is then explored in the Deep Learning world. You will evaluate the common, and not so common, deep neural networks and see how these can be exploited in the real world with complex raw data using TensorFlow. In addition, you will learn how to apply TensorFlow for backpropagation to tune the weights and biases while the Neural Networks are being trained. Finally, the course covers different types of Deep Architectures, such as Convolutional Networks, Recurrent Networks and Autoencoders.

Delve into neural networks, implement Deep Learning algorithms, and explore layers of data abstraction with the help of this Deep Learning with TensorFlow course.


- - - - - - - - - - - - - -

Who should go for this course?

The following professionals can go for this course:

1. Developers aspiring to be a 'Data Scientist'

2. Analytics Managers who are leading a team of analysts

3. Business Analysts who want to understand Deep Learning (ML) Techniques

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5. Professionals who want to captivate and analyze Big Data

6. Analysts wanting to understand Data Science methodologies

However, Deep learning is not just focused to one particular industry or skill set, it can be used by anyone to enhance their portfolio.

- - - - - - - - - - - - - -

Why Learn Deep Learning With TensorFlow?
TensorFlow is one of the best libraries to implement Deep Learning. TensorFlow is a software library for numerical computation of mathematical expressions, using data flow graphs. Nodes in the graph represent mathematical operations, while the edges represent the multidimensional data arrays (tensors) that flow between them. It was created by Google and tailored for Machine Learning. In fact, it is being widely used to develop solutions with Deep Learning.

For more information, please write back to us at sales@edureka.co or call us at IND: 9606058406 / US: 18338555775 (toll-free).

🔥Edureka Online Training: https://www.edureka.co
This Edureka video on 'Top 10 Web Frameworks in 2021' lists down the best frameworks that you can use to develop web applications.

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------------------------------------Edureka Online Training and Certification---------------------------------

🔵 DevOps Online Training: https://bit.ly/2BPwXf0
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For Online Training and Certification, Please write back to us at sales@edureka.co or call us at IND: 9606058406 / US: 18338555775 (toll free) for more information.

🔥𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐂𝐡𝐚𝐭𝐆𝐏𝐓 𝐂𝐨𝐮𝐫𝐬𝐞 - 𝐁𝐞𝐠𝐢𝐧𝐧𝐞𝐫𝐬 𝐭𝐨 𝐀𝐝𝐯𝐚𝐧𝐜𝐞𝐝: https://www.edureka.co/openai-....chatgpt-training-cou
This Edureka video on 𝐂𝐡𝐚𝐭𝐆𝐏𝐓 𝐀𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬 will talk about multiple use cases where you can use ChatGPT. There are several day to day applications where you can leverage ChatGPT to do the job for you. Below are some important ChatGPT applications covered in this ChatGPT tutorial:
00:00:00 Introduction
00:00:50 ChatGPT for Writing Code
00:02:25 ChatGPT for Code Debugging
00:03:37 ChatGPT for Content Writing
00:05:03 ChatGPT for SEO
00:06:18 ChatGPT for Language Translation
00:07:01 ChatGPT for Writing Legal Documents
00:08:11 ChatGPT for College Assignments
00:08:37 ChatGPT to make Workout Schedule

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📝Feel free to share your comments below.📝

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Statistical Learning, featuring Deep Learning, Survival Analysis and Multiple Testing

Trevor Hastie, Professor of Statistics and Biomedical Data Sciences at Stanford University - https://statistics.stanford.ed....u/people/trevor-j-ha

Robert Tibshirani, Professor of Statistics and Biomedical Data Sciences at Stanford University - https://statistics.stanford.ed....u/people/robert-tibs

Jonathan Taylor, Professor Statistics at Stanford University - https://statistics.stanford.ed....u/people/jonathan-ta

You are able to take Statistical Learning as an online course on EdX, and you are able to choose a verified path and get a certificate for its completion. You can choose to take the course in R (https://www.edx.org/course/statistica) or in Python (https://www.edx.org/learn/data....-analysis-statistics

For more information about courses on Statistics, you can browse our Stanford Online Catalog: https://stanford.io/3QHRi72

This is the Programming assignment 1 from Andrew Ngs Machine Learning course.

Github: https://github.com/AladdinPerz....on/Courses/tree/mast

Introducing the new Lambda Tensorbook – the world’s most powerful laptop for deep learning: https://rzr.to/lambda-tensorbook
Co-created with Lambda, this sleek laptop is powered by the latest NVIDIA GeForce RTX 3080 Max-Q 16GB GPU and machine learning tools including PyTorch to give engineers everything needed to create, train and test anytime, anywhere.

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