#algodevelopment search results

Got an edge? Contact us via DM, share it, and we'll help you develop and test it using our secret process that powers all our Algos. Let’s take your strategy to the next level—together. 🔥 #Trading #AlgoDevelopment #UnlockYourPotential

📢 Sharing the "meat and potatoes" of developing my trend following algo in public. An easy-to-do backtesting process that makes finding profitability. smartcrypto.substack.com/p/trend-follow… It's not glamourous. But the process works. #BuildInPublic #TrustTheProcess #AlgoDevelopment

Machine Learning (#3 of 3) * hyper-parameters in the Random Forest and Gradient Boosted Decision Tree algorithms * Briefly look at an LSTM neural network and the applicable code in Tensorflow. #MachineLearning #QuantTrader #AlgoDevelopment j.mp/2PuccLb

US Stock Market pre-market and post-market bid-ask spreads are different than regular trading hours. Data & Visualization created with CloudQuant backtesting. #AlgoDevelopment #StockMarket j.mp/2RfbCOK

Machine Learning & Quant Trading Part 2  - Preprocess data for Random Forest Classifier. Profit/Loss and prediction improvements. #MachineLearning #QuantTrader #AlgoDevelopment j.mp/2PybJI9

Pandas Cheat Sheet for Data Science in Python A quick guide to the basics of the Python data analysis library Pandas, including code samples. #Python #AlgoDevelopment j.mp/2Jjcy1D

A very easy way to avoid over-fitting is to do no fitting at all. Interview with Robert Carver. * What makes a good trading rule * The advantages of simple rules * Why only some trading rules are profitable #SystematicTrading #AlgoDevelopment j.mp/2PsUebO

Build a strong foundation for machine learning with quantitative trader Trevor Trinkino. A step-by-step introductory process for implementing ML and converting it into a trading algorithm using Python. #MachineLearning #AlgoDevelopment j.mp/2PwVkUl

Vol Targeting and Trend Following: volatility targeting - dynamically adjusting your positions according to your estimate of market volatility - in the context of trend following systems. Is this a good thing to do? #AlgoDevelopment #SystematicTrading j.mp/2PrlCae

NumPy Cheat Sheet: Data Analysis in Python #Python #AlgoDevelopment j.mp/2PlASW5

What is a Decision Tree in Machine Learning? Decision trees, one of the simplest and yet most useful Machine Learning structures. Decision trees, as the name implies, are trees of decisions. #MachineLearning #AlgoDevelopment j.mp/2EFYQYg

This Python cheat sheet is a handy reference with code samples for doing linear algebra with SciPy and interacting with NumPy. #Python #AlgoDevelopment j.mp/2EHFX78

Which Data Skills Do You Actually Need? Turning data into insight and action. Computing and mathematically-focused jobs are showing the strongest growth, at the expense of less quantitative roles. #DataScience #AlgoDevelopment j.mp/2Pgc41J

A handy scikit-learn cheat sheet to machine learning with Python, including code examples. #AlgoDevelopment #QuantitativeTrading j.mp/2PbvHrV

The 5 Basic Statistics Concepts Data Scientists Need to Know: * Statistical Features * Probability Distributions * Dimensionality Reduction * Over and Under Sampling * Bayesian Statistics #DataScience #AlgoDevelopment j.mp/2EFSiZv

Team CloudQuant discusses helpful thoughts for beginners to boost your #algoDevelopment and backtesting. We use our own app with every algo we in our daily algo trading. We rely on the scorecards & the simulation to ensure successful. j.mp/2vFg2WI

#AlgoDevelopment is best when you don’t have to worry about where your historical #marketdata comes from

A handy scikit-learn cheat sheet to machine learning with Python, including code examples. #AlgoDevelopment #QuantitativeTrading j.mp/2PbvHrV

Machine Learning (#3 of 3) * hyper-parameters in the Random Forest and Gradient Boosted Decision Tree algorithms * Briefly look at an LSTM neural network and the applicable code in Tensorflow. #MachineLearning #QuantTrader #AlgoDevelopment j.mp/2PuccLb

Machine Learning & Quant Trading Part 2  - Preprocess data for Random Forest Classifier. Profit/Loss and prediction improvements. #MachineLearning #QuantTrader #AlgoDevelopment j.mp/2PybJI9

NumPy Cheat Sheet: Data Analysis in Python #Python #AlgoDevelopment j.mp/2PlASW5

Build a strong foundation for machine learning with quantitative trader Trevor Trinkino. A step-by-step introductory process for implementing ML and converting it into a trading algorithm using Python. #MachineLearning #AlgoDevelopment j.mp/2PwVkUl

US Stock Market pre-market and post-market bid-ask spreads are different than regular trading hours. Data & Visualization created with CloudQuant backtesting. #AlgoDevelopment #StockMarket j.mp/2RfbCOK

This Python cheat sheet is a handy reference with code samples for doing linear algebra with SciPy and interacting with NumPy. #Python #AlgoDevelopment j.mp/2EHFX78

Team CloudQuant discusses helpful thoughts for beginners to boost your #algoDevelopment and backtesting. We use our own app with every algo we in our daily algo trading. We rely on the scorecards & the simulation to ensure successful. j.mp/2vFg2WI

Pandas Cheat Sheet for Data Science in Python A quick guide to the basics of the Python data analysis library Pandas, including code samples. #Python #AlgoDevelopment j.mp/2Jjcy1D

What is a Decision Tree in Machine Learning? Decision trees, one of the simplest and yet most useful Machine Learning structures. Decision trees, as the name implies, are trees of decisions. #MachineLearning #AlgoDevelopment j.mp/2EFYQYg

Which Data Skills Do You Actually Need? Turning data into insight and action. Computing and mathematically-focused jobs are showing the strongest growth, at the expense of less quantitative roles. #DataScience #AlgoDevelopment j.mp/2Pgc41J

A very easy way to avoid over-fitting is to do no fitting at all. Interview with Robert Carver. * What makes a good trading rule * The advantages of simple rules * Why only some trading rules are profitable #SystematicTrading #AlgoDevelopment j.mp/2PsUebO

Vol Targeting and Trend Following: volatility targeting - dynamically adjusting your positions according to your estimate of market volatility - in the context of trend following systems. Is this a good thing to do? #AlgoDevelopment #SystematicTrading j.mp/2PrlCae

The 5 Basic Statistics Concepts Data Scientists Need to Know: * Statistical Features * Probability Distributions * Dimensionality Reduction * Over and Under Sampling * Bayesian Statistics #DataScience #AlgoDevelopment j.mp/2EFSiZv