Muhammad Naeem (mnaeem95)

mnaeem95

Geek Repo

Company:Delivery Hero

Location:Berlin, Germany

Home Page:https://www.linkedin.com/in/mnaeemniazi/

Twitter:@mnaeemniazi95

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Muhammad Naeem's repositories

100-go-mistakes

Source code of 100 Go Mistakes 📖

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algorithms

My Algorithms and Data Structures studies. https://leandrotk.github.io/series/algorithms-problem-solving

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AutoWebPerf

AutoWebPerf provides a flexible and scalable framework for running web performance audits with arbitrary audit tools including PageSpeedInsights, WebPageTest and more.

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backendlore

How I write backends

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cassandra-workshop-series

All materials for the Cassandra Workshop Series in a single place

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commerce

Next.js Commerce

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ddd-cqrs-es-aws-sam

Comprehensive Domain Driven Design, CQRS, and Event Sourcing example utilizing AWS SAM.

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demo-v-microfronted-html-entrypoint

Demo project to build Micro Frontends with a Team-Based Vertical Architecture using html as entry point

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educative.io_courses

this is downloadings of all educative.io free student subscription courses as pdf from GitHub student pack

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example-consumer

An example of a consumer that uses Pact+Pactflow to create a consumer driven contract with its provider

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example-provider

An example of a provider that uses Pact+Pactflow to honour a consumer driven contract with its consumer

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just-react

React技术揭秘

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learn-istio

⛵️ Istio resources 🕸

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machine-learning-for-trading

Code for Machine Learning for Algorithmic Trading, 2nd edition.

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react-native-web-monorepo

Code sharing between iOS, Android & Web using monorepo

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sabbar-take-home-challenge

Sabbar Take Home Challenge

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solution-architecture-patterns

Reusable, vendor-neutral, industry-specific, vendor-specific solution architecture patterns for enterprise

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Stock-Prediction-Models

Gathers machine learning and deep learning models for Stock forecasting including trading bots and simulations

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stockpredictionai

In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.

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strong-node

:heavy_check_mark: More than 100 security checks for your Node.js API

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talent-plan

open source training courses about distributed database and distributed systemes

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type-challenges

Collection of TypeScript type challenges with online judge

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typescript-event-sourcing

Domain Driven Design, Event Sourcing & Command Query Responsibility Segregation with Typescript

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ultimate-backend

Multi tenant SaaS starter kit with cqrs graphql microservice architecture, apollo federation, event source and authentication

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v8-perf

⏱️ Notes and resources related to v8 and thus Node.js performance

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