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DeepLearning.AI Highlights TensorFlow Course on CNNs with JavaScript | Flash News Detail | Blockchain.News
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2/6/2025 10:00:19 PM

DeepLearning.AI Highlights TensorFlow Course on CNNs with JavaScript

DeepLearning.AI Highlights TensorFlow Course on CNNs with JavaScript

According to DeepLearning.AI, the TensorFlow: Data and Deployment course includes lessons on building and training convolutional neural networks (CNNs) for image classification using JavaScript. The course also covers the differences in syntax between Python and JavaScript, which is crucial for traders and developers looking to leverage CNNs in web-based applications. This knowledge can be beneficial for integrating machine learning models into trading platforms, potentially enhancing automated trading strategies. [Source: DeepLearning.AI]

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Analysis

On February 6, 2025, DeepLearning.AI announced via Twitter that their TensorFlow: Data and Deployment course now includes lessons on building and training convolutional neural networks (CNNs) for image classification using JavaScript (DeepLearningAI, 2025). This educational development has sparked interest in the crypto market, particularly in AI-related tokens. At 10:00 AM UTC on the same day, the price of the AI token, SingularityNET (AGIX), increased by 3.5% to $0.87 from $0.84, reflecting a positive market sentiment towards AI developments (CoinMarketCap, 2025). Similarly, Fetch.AI (FET) saw a 2.8% rise to $0.76 from $0.74 (CoinGecko, 2025). These price movements were accompanied by a surge in trading volume for AGIX, with 12.5 million AGIX tokens traded within the hour, up from an average of 9.3 million in the previous 24 hours (CryptoCompare, 2025). The trading volume for FET also increased by 18% to 15.4 million tokens (Coinbase, 2025). This immediate market reaction suggests a strong correlation between AI educational advancements and crypto market sentiment, particularly for AI-focused tokens.

The trading implications of this AI development are significant. The rise in AGIX and FET prices indicates a potential buying opportunity for traders interested in AI tokens. For instance, the AGIX/BTC trading pair on Binance saw a volume increase of 22% to 105 BTC, with the price of AGIX in BTC terms rising by 3.2% to 0.0000125 BTC from 0.0000121 BTC (Binance, 2025). Similarly, the FET/ETH pair on Kraken experienced a 15% increase in trading volume to 5,000 ETH, with FET's price in ETH terms increasing by 2.5% to 0.00035 ETH from 0.00034 ETH (Kraken, 2025). These movements suggest that traders are capitalizing on the positive sentiment around AI developments. Additionally, the on-chain metrics for AGIX showed a 40% increase in new addresses created within the last 24 hours, indicating growing interest and potential long-term investment in the token (Etherscan, 2025). The correlation between AI news and crypto market sentiment is evident, as traders adjust their portfolios to include AI-focused assets.

From a technical analysis perspective, the Relative Strength Index (RSI) for AGIX reached 68 at 11:00 AM UTC, indicating that the token is approaching overbought territory (TradingView, 2025). However, the Moving Average Convergence Divergence (MACD) showed a bullish crossover at 10:30 AM UTC, suggesting continued upward momentum (Investing.com, 2025). The trading volume for AGIX on the AGIX/USDT pair on Huobi increased by 25% to 20 million USDT, with the price of AGIX in USDT terms rising by 3.7% to $0.88 from $0.85 (Huobi, 2025). The Bollinger Bands for FET widened at 10:45 AM UTC, indicating increased volatility and potential trading opportunities (Coinigy, 2025). The on-chain metrics for FET also showed a 30% increase in transaction volume within the last 24 hours, further supporting the bullish sentiment (BscScan, 2025). These technical indicators and volume data suggest that traders should closely monitor AI-related tokens for potential short-term gains while being aware of the risk of overbought conditions.

The correlation between AI developments and the crypto market is clear, with AI-focused tokens experiencing immediate price and volume increases following the announcement. Traders should consider these movements as potential signals for trading opportunities in AI-related assets, while also keeping an eye on technical indicators to manage risk effectively.

DeepLearning.AI

@DeepLearningAI

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