- Want to Join a Bank? Everything Data Scientists Need to Know About Working in Fintech - Oct 28, 2021.
There is ample opportunity for data scientists in the financial services sector. The career experience can be very different, however, from similar roles at pure technology organizations. So, it's best to first consider if this industry is right for your interests, preferences for how you work, and long-term goals.
Career Advice, Data Scientist, Finance, Fintech
- How I Built A Perfect Model And Got Into Trouble - Oct 12, 2021.
Data-driven decisions, actionable insights, business impact—you've seen these buzzwords in data science jobs descriptions. But, just focusing on these terms doesn't automatically lead to the best results. Learn from this real-world scenario that followed data-driven indecisiveness, found misleading insights, and initially created a negative business impact.
Analytics, Business, Customer Analytics, Finance, KPI, Metrics
- Building a Structured Financial Newsfeed Using Python, SpaCy and Streamlit - Sep 28, 2021.
Getting started with NLP by building a Named Entity Recognition(NER) application.
Finance, NLP, Python, spaCy, Streamlit
- 9 Outstanding Reasons to Learn Python for Finance - Sep 23, 2021.
Is Python good for learning finance and working in the financial world? The answer is not only a resounding YES, but yes for nine very good reasons. This article gets into the details behind why Python is a must-know programming language for anyone who wants to work in the financial sector.
Finance, Python
- The Top Industries Hiring Data Scientists in 2021 - Aug 30, 2021.
People realize that effective uses of data can increase competitiveness, even in a challenging marketplace. Here are six industries hiring data scientists now that will likely continue doing so for the foreseeable future.
Career Advice, Finance, Insurance, Life Science, Telecom
- Major changes: Where Analytics, Data Science, Machine Learning were applied in 2020/21 - Jun 18, 2021.
Our latest poll shows major change in where AI, Data Science, Machine Learning are being applied, with decline in interest in traditional fields like CRM/Consumer Analytics, and growth in applications to Computer Vision, COVID, Agriculture, and Education.
Agriculture, Computer Vision, Consumer Analytics, Education, Finance, Industry, Poll
- Deep Learning in Finance: Is This The Future of the Financial Industry? - Jul 10, 2020.
Get a handle on how deep learning is affecting the finance industry, and identify resources to further this understanding and increase your knowledge of the various aspects.
Deep Learning, Finance
- Pull and Analyze Financial Data Using a Simple Python Package - Jul 9, 2020.
We demonstrate a simple Python script/package to help you pull financial data (all the important metrics and ratios that you can think of) and plot them.
Finance, Pandas, Python
- Free Economics & Finance Courses for Data Scientists - Jun 25, 2020.
Here is a selection of courses for those interested in diversifying their domain knowledge into the related realms of economics and finance, with the goal of being able to apply your data science skills to these domains.
Courses, Economics, Finance, MOOC
- Four Ways to Apply NLP in Financial Services - Jun 2, 2020.
Natural language processing (NLP) is increasingly used to review unstructured content or spot trends in markets. How is Refinitiv Labs applying NLP in financial services to meet challenges around investment decision-making and risk management?
Finance, NLP
- Spotting Controversy with NLP - May 21, 2020.
In this article, I’ll introduce you to a hot-topic in financial services and describe how a leading data provider is using data science and NLP to streamline how they find insights in unstructured data.
BERT, Finance, Fintech, NLP
- Time Series Classification Synthetic vs Real Financial Time Series - Mar 18, 2020.
This article discusses distinguishing between real financial time series and synthetic time series using XGBoost.
Finance, R, Time Series, XGBoost
- How to Get Started With Algorithmic Finance - Jan 23, 2020.
Algorithmic finance has been around for decades as a money-making tool, and it's not magic. Learn about some practical strategies along with and introduction to code you can use to get started.
Algorithms, Finance, Hedge fund, Investment, Time Series
- Stock Market Forecasting Using Time Series Analysis - Jan 9, 2020.
Time series analysis will be the best tool for forecasting the trend or even future. The trend chart will provide adequate guidance for the investor. So let us understand this concept in great detail and use a machine learning technique to forecast stocks.
Analysis, Finance, Forecasting, Stocks, Time Series
- Optimization with Python: How to make the most amount of money with the least amount of risk? - Jun 26, 2019.
Learn how to apply Python data science libraries to develop a simple optimization problem based on a Nobel-prize winning economic theory for maximizing investment profits while minimizing risk.
Finance, Investment, Optimization, Python, Risk Modeling, Stocks
- How AI can help solve some of humanity’s greatest challenges – and why we might fail - Feb 12, 2019.
AI represents a step change in humanity’s ability to rise to its greatest challenges. We explore three areas in which AI can contribute to the UN’s Global Goals - and why we could fall short.
AI, Finance, Healthcare, Innovation, Social Good, United Nations
- Top 5 domains Big Data analytics helps to transform - Nov 23, 2018.
Big data analytics gives a competitive advantage to companies across many industries, especially, financial services, e-commerce, aviation, transportation, logistics, and energy. It enables to reduce downtime, mitigate risks, cut costs, and improve performance.
Aviation, Big Data, Big Data Analytics, Credit Risk, Data Analytics, Ecommerce, Finance, Security
- Using a Keras Long Short-Term Memory (LSTM) Model to Predict Stock Prices - Nov 21, 2018.
LSTMs are very powerful in sequence prediction problems because they’re able to store past information. This is important in our case because the previous price of a stock is crucial in predicting its future price.
Finance, Keras, LSTM, Neural Networks, Stocks
- Financial Data Analysis – Data Processing 1: Loan Eligibility Prediction - Sep 4, 2018.
In this first part I show how to clean and remove unnecessary features. Data processing is very time-consuming, but better data would produce a better model.
Data Preprocessing, Data Processing, Finance, Python
- Reinforcement Learning: The Business Use Case, Part 2 - Aug 16, 2018.
In this post, I will explore the implementation of reinforcement learning in trading. The Financial industry has been exploring the applications of Artificial Intelligence and Machine Learning for their use-cases, but the monetary risk has prompted reluctance.
Business, Finance, Machine Learning, Reinforcement Learning, Use Cases
- Enhancing Anti-Money Laundering Programs with Automated Machine Learning, Jan 11 Webinar - Jan 3, 2018.
In this webinar, Jan 11, DataRobot will show how automated machine learning can be used to reduce false positive rates, thereby improving the efficiency of AML transaction monitoring and reducing costs.
Automated Data Science, Automated Machine Learning, DataRobot, Finance, Money Laundering
- 70 Amazing Free Data Sources You Should Know - Dec 20, 2017.
70 free data sources for 2017 on government, crime, health, financial and economic data, marketing and social media, journalism and media, real estate, company directory and review, and more to start working on your data projects.
Big Data, Business, Crime, Datasets, Finance, Government, Health, Journalism, Octoparse, Social Media
- TensorFlow for Short-Term Stocks Prediction - Dec 12, 2017.
In this post you will see an application of Convolutional Neural Networks to stock market prediction, using a combination of stock prices with sentiment analysis.
Convolutional Neural Networks, Finance, Python, Stocks, TensorFlow
- A Guide For Time Series Prediction Using Recurrent Neural Networks (LSTMs) - Oct 5, 2017.
Looking at the strengths of a neural network, especially a recurrent neural network, I came up with the idea of predicting the exchange rate between the USD and the INR.
Pages: 1 2
Finance, LSTM, Neural Networks, Recurrent Neural Networks, Statsbot
- Top 10 Videos on Machine Learning in Finance - Sep 29, 2017.
Talks, tutorials and playlists – you could not get a more gentle introduction to Machine Learning (ML) in Finance. Got a quick 4 minutes or ready to study for hours on end? These videos cover all skill levels and time constraints!
Credit Risk, Finance, Investment Portfolio, Machine Learning, Python, R, Stocks, Tutorials, Videolectures, Youtube
- Global Big Data Conference, Santa Clara, Aug 29-31 – KDnuggets Offer - Aug 14, 2017.
Global Big Data Conference, a leading vendor agnostic conference for the Big Data community, will hold 5th conference in Santa Clara. Use code KDnuggets to save.
Big Data, CA, Finance, Global Big Data Conference, Industry, Santa Clara
- Spotlight on the Remarkable Potential of AI in KYC (Know Your Customer) - Jul 4, 2017.
Most people would have heard of the headline-making tremendous achievements in artificial intelligence (AI): Systems defeating world champions in board games like GO and winning quiz shows. These are small realizations of AI, but there is a silent revolution taking place in other areas, including Regulatory Compliance in Financial Services.
AI, Compliance, Customer Research, Finance, Money Laundering
- Unsupervised Investments: A Comprehensive Guide to AI Investors - Mar 24, 2017.
This article presents a list of 80 funds investing in Artificial Intelligence and Machine Learning.
AI, Finance, Investment
- Data Analytics Models in Quantitative Finance and Risk Management - Dec 13, 2016.
We review how key data science algorithms, such as regression, feature selection, and Monte Carlo, are used in financial instrument pricing and risk management.
Data Analytics, Feature Selection, Finance, Regression, Risk Modeling
- Awesome Public Datasets on GitHub - Apr 6, 2015.
A long, categorized list of large datasets (available for public use) to try your analytics skills on. Which one would you pick?
Pages: 1 2
Datasets, Finance, GitHub, Government, Machine Learning, NLP, Open Data, Time series data