St Louis
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8 min readAutomatic differentiation is a crucial component of machine learning frameworks like TensorFlow that allows us to compute derivatives efficiently. TensorFlow provides a built-in mechanism for automatic differentiation, enabling us to calculate gradients of scalar functions with respect to variables efficiently.To implement automatic differentiation in TensorFlow, we follow these steps:Define variables: Start by creating the variables that you want to differentiate with respect to.
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13 min readThe Price Rate of Change (ROC) is a technical indicator that measures the percentage change in price over a specified period of time. It is calculated by taking the current price and comparing it to the price at a certain point in the past. The ROC is commonly used by traders and analysts to gauge the momentum and strength of a particular security or market.
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9 min readDebugging TensorFlow models can be a complex task, but there are several techniques that can help you do it effectively. Here are some strategies to consider:Print statements: One of the simplest ways to debug TensorFlow models is by inserting print statements at various points in your code to check the values of tensors, variables, or any other relevant information. Print statements can help you identify errors or unexpected behavior.
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10 min readBreakout trading is a popular strategy used in various financial markets, including stocks, forex, and commodities. The purpose of a breakout trading strategy is to identify and capitalize on significant price movements that occur when the price breaks out of a defined range or level of support/resistance.Designing an effective breakout trading strategy involves several key steps.
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10 min readOn-Balance Volume (OBV) is a technical analysis tool and indicator used in the field of stock market analysis. It was developed by Joseph Granville and is designed to forecast changes in the price of a security by tracking the volume traded over a specific period of time.The main concept behind OBV is that volume is an important factor in determining the direction of a stock's price movement.
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8 min readIntegrating TensorFlow with other deep learning frameworks can be done in several ways depending on the specific requirements and frameworks involved. Here is an overview of some common methods:TensorFlow as a backend: In this approach, TensorFlow is used as a backend for other deep learning frameworks such as Keras or PyTorch. This allows you to leverage the power of TensorFlow while using the high-level abstractions and simplicity of other frameworks.
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7 min readVolume analysis is a popular technique used in trading to gain insights into the overall market activity surrounding a particular asset. It involves analyzing the trading volume, or the total number of shares or contracts traded during a specific time period. By incorporating volume analysis into your trading strategy, you can gain a deeper understanding of market trends, price movements, and potential reversals.
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13 min readMoving Average Convergence Divergence (MACD) is a popular technical indicator used in scalping strategies by traders in the financial markets. It is a trend-following momentum indicator that shows the relationship between two moving averages of an asset's price.MACD consists of three components: the MACD line, the signal line, and the histogram. The MACD line is calculated by subtracting the 26-day exponential moving average (EMA) from the 12-day EMA.
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7 min readDistributed training in TensorFlow allows you to train machine learning models on multiple devices or machines simultaneously, enabling faster and more efficient model training. Here, we will discuss the key concepts and steps involved in using distributed training in TensorFlow.To begin, distributed training requires a cluster of devices or machines that work together to train the model.
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6 min readConstructing a trend-following trading strategy involves several key steps. Here's a detailed explanation of the process:Identify the Timeframe: Determine the timeframe you want to trade based on your investment goals and risk tolerance. Common timeframes for trend-following strategies include daily, weekly, or monthly charts.
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17 min readThe Average True Range (ATR) is a popular technical indicator used to measure volatility in the financial markets. It provides traders with valuable information about potential price movements and can be particularly helpful for determining stop-loss levels and setting profit targets.To interpret the ATR, beginners should understand the following key points:Volatility measurement: The ATR measures the average range between the high and low prices of an asset over a specified period.