Having a data set with gene expressions from colon \ncancer, we aimed to construct a new feature to \nimprove machine learning\n classification task.\nKey words:\nfeature extraction, gene expression, machine le\narning, logistic regres\nsion, Dan Barbilian, \ndata science, colon cancer, genes, associated genes

EXperimental results using Self Organizing Maps (SOM) also called Kohonen neural \nnetworks for analyzing systolic hypertension using clinical and bio clinicalparameters. \nWe have conducted experiments using Sompy library available as open source in Python on 900 diabetes patients and concluded this particular type of artificial neural networks could learn patterns regarding correlation of systolic hypertension with different other clinical or bioclincal values, which we consider surprising due to \nthe fact self organizing detects domain knowledge in data. \n

Developed project for the PowerforAlls data analysis project. Integrated a lot of often source code to the Django project and auto indexing documents with opensemanticsearch tool and visualize data with HighCharts and Mapbox.

Quantitative Data Analysis using IBM SPSS. Various statistical procedures were used including: regression, correlation and moderation.

Developing a stock trading strategy requires money and time. You may face all sorts of frustrations as a beginner since emotions drive your decisions in the early stages. However, recognizing market conditions and formulating a trading plan is becoming more vital. You must find the best technical analysis tool that suits your goals, risk tolerance, and personality. Traders realize their suitable technical analysis tools differently and at different stages. Some traders can now learn from managing other investors’ market flow via online retail FX trading. Generally, technical trading strategies feature three basic principles that you can master better through close retail market flow observation. These principles include momentum, time, and price. Price Value Effective trading is more than the current price relative levels. You need to identify resistance and support to create any actionable trade plans that counter or target key price levels. Numerous methods are now available to help you identify these average directional index levels. The three most effective ones include Low | High Closes, Fibonacci & Key Reversals. Fibonacci is a popular approach that provides simple measurements based on the 61.8% golden ratio. Thus, it can help predict and leverage the trading markets’ behavior. It provides an effective tool that you can apply for both range bound and trading markets to identify a possible positive and negative flow. Time Value Another functional approach is the median line analysis to assess the trend and slope lines. This approach seeks to identify the gradient or slope of any given market, highlighting points where a significant shift in the price level can occur. It is now an efficient time value identifier that adds to other lateral levels. Hence, traders can identify “confluence zones” that pinpoint time and prices with major pivots in near time price action. Trading off & in these inflection pinpoints can be the best technical trade setups. Momentum Value (RSI) Traders can now formulate the RSI (Relative Strength Index) from the market speed. The RSI describes an oscillator that applies as a momentum measure to help predict the price movement direction and speed. Although most oscillators are backward looking, they can help you assess when the stock market might get overextended in oversold or overbought situations. Assessing stock market inertia is vital for trend trading and near term swing. It provides a window for possible strength and longevity of any trading idea and when it may expire. Final Remarks Formulating a multi faceted trading plan based on time value, momentum, and price value are crucial. It can help avoid failure and also allow more opportunities. Above all, style trading works on balance volume indicator and trend indicator. Moving average convergence divergence, chart patterns, cost average, and momentum indicator are crucial.

The latest sanctions expansion on the Russian financial sector seeks to disconnect her three largest banks from the global payment networks. Targeted banks include the state owned Sberbank. In general, Sberbank is Russia’s top lender. Other banks are the Russian Agricultural Bank and the Credit Bank of Moscow. This report comes following a European Union agreement. Ursula von der Leyen (the EU president) said that this sanction will hinder most systemically vital banks to the country’s financial system. The sanction also aims to shrink Putin’s wage destruction ability. Several Russian major banks like the VTB (second largest bank) have already pushed off SWIFT. Nonetheless, the European Union has slowed confiscating banks like Sberbank that handle energy transactions. Experts now believe this move might mean less impact since other sanctions now seek to phase out Russia crude oil imports within six months. The Sberbank accounts for about 37% of the Russian financial system. Thus, Russia's banking disconnection from SWIFT is a massive blow to her fragile economy. Russia is increasingly facing cut off from their finance mainstream. SWIFT is not a transfer system, but it generates messages to authorize and support payments. Thus, it is a vital factor for the easy functioning of financial institutions. The system processes more than 40 million messages daily. The EU president explained that disconnecting Russian banks from SWIFT would help solidify Russia’s total isolation and suspension from the global system. However, experts contemplate that Russia might seek refuge in SWIFT alternatives. What's the Impact on Russian Banks? Russia established the SPFS (System Transfer of Financial Messages) in 2014. It is the country’s independent ruble based exchange system. They also have access to other options like the CIPS (China’s Interbank Payment System). In any case, the SPFS is the most popular transaction system for most hit banks in Russia. It is also a popular option for about 52 foreign organizations in more than 12 countries. Nevertheless, the Russian Central Bank has refrained from naming other users. Putin’s administration has persuaded several emerging economies to opt for the SPFS system. The most targeted countries include South Africa, China, India, Russia, and Brazil. Anton Siluanov (Russian Finance Minister) warned these countries in a BRICS ministerial meeting to learn from the sanctions they face in the world financial systems. He advocated speeding up their own financial messaging system and payment systems integration. Furthermore, China and Russia are working together to establish a connection between their financial systems to facilitate Asian payments. Other reports indicate that China is still purchasing cheap oil from Russia despite the threats of breaking sanctions. Final Remarks The crisis in Ukraine is worsening, and more people have lost their livelihood. Hence, the European Union is stringent about imposing severe sanctions on Russia to help curb the invasion. Sanctions play a crucial role in keeping nations compliant with human rights. Nonetheless, this approach faces challenges from countries like China that are sidelining Russia. For that reason, the European Union has warned to impose intense penalties on Russia’s counterparts.

Gathers pricing research in an automotive for car parts such as brake disc, brake pads, brake calipers and many others. Using part number or the Year/make/model in each item check different sites of competitors to get the actual price and links as reference.

Here we have a quantitative mean reverting indicator with buy and sell signals