Burak Akal

A results-driven Machine Learning Engineer and Data Scientist (certified by Microsoft, Google and Databricks) with a track record in delivering/optimising data-driven solutions for over 10 years. Expert in translating business needs into impactful Machine Learning / Data Science applications, leveraging an ideal blend of soft and technical skills honed through a wide variety of projects.
Passionate about innovative leadership and utilising cutting-edge tech to solve complex problems; challenges the status quo, upskills the team, and builds effective partnerships with key stakeholders

My Portfolio

• All
• Soft Skills
• Machine Learning
• Algoritmic Trading
• Lectures

Soft Skills

Leadership and Innovative Leadership

Soft Skills

Stakeholder Management

Machine Learning, Algorithmic Trading

My Algo Trading App

Margin Day Trade Algorithmic Trading - Powered by Artificial Neural Network

Predicting stock market trends accurately is a challenge that has long perplexed even the most experienced investors. Not only is there the well-known adage that "past performance is no guarantee of future results" but also, any patterns that are detected are often short-lived. Despite these hurdles, can consistent profits be achieved by leveraging a machine learning prediction model within an algorithm? In my opinion, the answer is yes. While it may be impossible to predict every single outcome for every stock at all times, the vast scale/diversity of the stock market instruments allows for identifying patterns for some instruments, sometimes.

The key to success lies in modelling, training method, and simulation (also known as backtesting). The goal is to build a model that can encapsulate the chaotic nature of the stock market, followed by remaining vigilant about rapidly changing trends and simulating the very nature of the chaos through methods such as Monte Carlo or time-series k-fold cross-validation. The winning model is not necessarily the one that returned the highest profit, but the one with the most consistent profit. You can download the diagram of the production app from the link below. Please note that my app is non-commercial and used for my own personal investment decisions only. None of the information provided on my website should be regarded as financial advice.

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Machine Learning

OpenStreetMap: Unsupervised ML for making user-entered Tags meaningful

Machine Learning, Lectures

Regression: Diagnose and optimise [Neural Networks, Random Forest, Linear]

Machine Learning, Lectures

Regression: Practical understanding and making your own realistic dataset

Education

Skills

Programming Languages & Tools

Certifications

• Google Cloud: Professional Machine Learning Engineer
• Microsoft Certified: Azure Data Scientist Associate
• Databricks: Large Language Models: Application through Production
• APMG International: AgilePgM® Foundation
• British Quality Foundation: Six Sigma Black Belt + Lean Six Sigma Advanced Green Belt
• BT Internal Training: Change Management Advanced
• NVQ: Management QCF Level 3

Interests

I love long-distance cycling 🚲 I like to ride my hybrid bike at a relaxed pace and explore the countryside. It's a great way to enjoy the outdoors and discover new places. My go-to routes include the Kent coastline from Gravesend to Ramsgate, London to Cambridge, Loughton to Aylesbury, and the Karpaz Peninsula in Cyprus where donkeys roam free.

When I'm not cycling, I enjoy having picnics in woodlands or by lakes. I love connecting with nature 🌳 and checking out all the living creatures in their natural habitat. It brings me back to my childhood and is a great way to enjoy any season.

I'm a sci-fi fan, especially the cyberpunk sub-genre 🤖 (shouldn't come as a surprise if you read this far!). Black Mirror by Charlie Brooker is my favourite series, and I can't wait for the new series to drop. Another favourite of mine is Inception by Christopher Nolan - was it a dream or not at the ending? I reckon it was a dream...